CUASI NOMÁS INGLÉS: PROSODY at the CROSSROADS of SPANISH and ENGLISH in 20TH CENTURY NEW MEXICO Jackelyn Van Buren Doctoral Student, Linguistics

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Fall 11-15-2017 CUASI NOMÁS INGLÉS: PROSODY AT THE CROSSROADS OF SPANISH AND ENGLISH IN 20TH CENTURY NEW MEXICO Jackelyn Van Buren Doctoral Student, Linguistics

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Jackelyn Van Buren Candidate

Linguistics Department

This dissertation is approved, and it is acceptable in quality and form for publication:

Approved by the Dissertation Committee:

Dr. Chris Koops, Chairperson

Dr. Naomi Lapidus Shin

Dr. Caroline Smith

Dr. Damián Vergara Wilson

CUASI NOMÁS INGLÉS: PROSODY AT THE CROSSROADS OF SPANISH AND ENGLISH IN 20TH CENTURY NEW MEXICO

JACKELYN VAN BUREN

B.A., Linguistics, University of Utah, 2009 M.A., Linguistics, University of Montana, 2012

DISSERTATION

Submitted in Partial Fulfillment of the Requirements for the Degree of

Doctor of Philosophy in Linguistics

The University of New Mexico Albuquerque, New Mexico

December 2017

Acknowledgments

A dissertation is not written without the support of a community of peers and loved ones. Now that the journey has come to an end, and I have grown as a human and a scholar and a friend throughout this process (and have gotten married, become an aunt, bought a house, and gone through an existential crisis), I can reflect on the people who have been the foundation for every change I have gone through. The future is unknown, but the past is behind me (or ahead of me, as Laura Hirrel would point out), and I would like to thank each of you for being a part of this mad and exhilarating experience that has been getting a Ph.D. in the time of tumultuous politics and anti-intellectualism.

First, to the professors who have made a positive difference in my life. I have been lucky to go to a university with an uplifting community of researchers who emit an energy of passion and attention to their work and their students. Dr. Naomi Shin, you were the first person to introduce me to the world of Spanish Linguistics and to quantitative research. I was in awe attending the first class I ever took of yours; what an amazing and talented teacher! Students who come across you are incredibly lucky because if they are committed, you give them the world in terms of mentorship and opportunity. Many times I pushed myself to be worthy of what you offered. Thank you for all the years you have been my mentor and my friend. I hope our paths cross again.

To Dr. Chris Koops: I do not know how to form into words the amount my life has benefited from knowing you and from being your student. I would not have a Ph.D. today if it weren’t for you, and that honor is something I will hold near and dear to my heart for the duration of my life. You are an excellent professor and students at UNM are luckier than they could ever realize to study under you. I have thoroughly enjoyed all the

iii discussions I have had with you about language and history. Thank you for being the best dissertation chair anyone could ever hope for. I also hope our paths cross again.

I could write a page about each of the following professors who have made a positive impact on my life and my time here at UNM, but I am afraid that the dissertation is becoming impatient, so I will be brief. To Dr. Caroline Smith, thank you for sharing your brilliance with me and with your students. Usage-based phonology remains one of the most intellectually stimulating and exciting classes I have ever taken. Thank you also for being a part of my committee, and for giving me helpful feedback that simultaneously pushed me outside of my comfort zone and made me a better scholar. To Dr. Damián

Vergara Wilson, thank you for being such a positive source of mentorship. It is rare to be so simpático and yet so exacting. You make students want to be better scholars, and at the same time encourage their passion and unique voice. I am so grateful I got to know you and that you agreed to be on my committee. Thank you.

To Dr. Melissa Axelrod, Dr. Rosa Vallejos-Yopán, Dr. Dawn Nordquist, Dr. Jill

Morford, Dr. Barbara Shaffer, Dr. Sherman Wilcox, and Dr. Richard File-Muriel, you are amazing professors and are all faces I look forward to seeing when I come to the department. Thank you for all you do for your students and for the support and encouragement you take the time to give us. It makes a difference.

I would also like to thank the UNM-Mellon Foundation for providing me with the financial support to complete my dissertation. I can honestly say I would never have been able to finish on time without it. I would specifically like to thank Dr. Michael Graves and Dr. Adriana Ramirez de Arellano for their guidance and supportive mentorship.

Adriana, you were the bright spot at the end of every month. Thank you for making me laugh and showing me that smart women could take over the world.

In the years it takes to complete a Ph.D., many strong friendships and shared experiences are formed. I could not have done this without the following group of peers who made it bearable (and even enjoyable): Keiko Beers, Josefina Bittar, Pavlina

Peskova, Rebeca Martínez Gomez, Ricardo Napoleão de Souza, Sara Siyavoshi, Laura

Hirrel, Andres Mauricio Sabogal, Robert Cruz, Benjamin Anible, Chris Peverada, David

Paez Acevedo, Debbie Wager, Nathan Bush, Susan Brumbaugh, Julia Remsik, Ryan

Smith, Samuel Melada, Len Beké, Carlos Enrique Ibarra, Desirée Ramírez-Urbaneja, and

Michael Woods. Thank you all for making the time here better, and for being friends. I hope all our paths cross again.

There is one colleague I did not mention above, because she more than any other friend has made the biggest difference in my time here and has always made me feel loved, especially when I needed it most. Thank you to Dr. Aubrey Healey for being the best part (aside from my husband) of my time spent in New Mexico. We created so many unforgettable memories together, including a bachelorette party, four Halloweens, a few

New Year celebrations, and plenty of commiseration with laughs and smiles and just a little bit of sweat and tears. Thank you for the amazing friendship you have given me. I know we will meet again many, many times.

Finally, to my family. The home we are born into is the first lottery in life, and I am so lucky for the one I was given. My parents are my biggest fans, and have always encouraged me to follow my dreams. I wake up every day feeling grateful for all they have given me, and grateful that I have parents who believe in me, even when my faith in

v myself falters. Thank you for everything you have done for me. I promise that when I have a good job I will take care of you and take you guys on cruises. Especially you, mi mamá. Thank you to my sister, Franchesca, for always pushing me to be the best version of myself because you knew I had it in me. Thank you to my brother-in-law Dylan for bringing some humor to the family, and for accepting me as a little sister.

Finally, finally, to the best guy I have ever met, to the guy who asked me to marry him and in so doing gave me hope for a beautiful future: Jeff Vanden Heuvel. Thank you for your support and encouragement along the way, and to always believing that I could finish. In many ways, you went through this process with me, and felt the stress when I felt it, even as you made me feel better and cared for me. I love you with all my heart, and I can’t wait for our next journey. Thank you also for the second family you have given me; to Charlene, Chris, Jack, and Sarah, thank you for accepting me into your family and for supporting me along this journey. I am lucky to know you.

CUASI NOMÁS INGLÉS: PROSODY AT THE CROSSROADS OF SPANISH AND ENGLISH IN 20TH CENTURY NEW MEXICO

JACKELYN VAN BUREN

B.A., Linguistics, University of Utah, 2009 M.A., Linguistics, University of Montana, 2012 Ph.D., Linguistics, University of New Mexico 2017

ABSTRACT

This dissertation investigates prosodic change in the long-term language contact setting of

Traditional New Mexican Spanish (NMS). NMS prosody is perceptually distinct from other contemporary varieties of Spanish (Hills 1906, Bowen 1952, Lipski 2011), yet the features which make it unique have not been acoustically examined. This study hypothesizes that bilingualism with English has affected NMS prosody and analyzes three features which are known to differ between Spanish and English and therefore provide a quantitative point of comparison: pitch peak alignment, pitch variability, and rhythmic timing. These variables have been demonstrated to be susceptible to transfer in contact situations, including Spanish-English settings. This study asks whether NMS prosody has remained relatively stable over the 20th century or whether patterns have changed in a more English-like direction. This study also asks whether socio-demographic and language use factors correlate with change in Spanish prosodic patterns. This study answers these questions using naturalistic speech from 60 speakers in the New Mexico

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Colorado Spanish Survey (NMCOSS) (Bills & Vigil 2008). Participants in the NMCOSS have birth dates that span approximately 100 years (1897-1978), precisely the period that saw the change from a Hispanic majority to a Hispanic minority in New Mexico concomitant with an increase in English-Spanish societal bilingualism.

Results of the mixed-effects regression analyses indicate that there is no evidence for change in apparent-time, demonstrating that the features considered in this study have not significantly changed in a more English-like direction throughout the 20th century. In particular, speakers retain the delayed peak alignment pattern typical of pre-nuclear broad focus declarative pitch accents in monolingual varieties of Spanish. Regarding rhythmic timing, measured using the PVI formula (Low & Grabe 1995), findings suggest that rhythmic timing in New Mexican Spanish has remained relatively stable across the three generations in this sample (mean PVI = .36), and there are no clear indications of influence from English. Regarding pitch variability, also measured using the PVI formula, younger speakers were expected to exhibit more pitch variability due to influence from

English, which is reported to have a wider pitch range than Spanish (Kelm 1995, Enzinna

2015, Navarro Tomás 1944, Stockwell & Bowen1965, Cruttenden 1986). While Age was found to significantly correlate with pitch PVI, it was not in the expected direction; it was found that as the age of the speaker decreases, the less likely they are to exhibit more pitch variability.

In sum, the analysis of prosodic features in this study suggests NMS has remained

relatively impervious to English influence. This study provides a picture of the situation

of language contact between Spanish and English in New Mexico, and how this speech

community has been resistant to change from English, suggesting that social factors

viii should be considered along with linguistic factors when discussing prosodic change in contact situations. This study adds to the literature on prosodic variation in Spanish, including Spanish in the United States. Thus, this dissertation study contributes to the fields of sociophonetics, language contact, and bilingualism.

Table of Contents List of Figures ...... xiii List of Tables ...... xvii Chapter One: Introduction ...... 1 1.1. Research Questions and Hypotheses ...... 8 Chapter Two: Historical and Linguistic Background of the New Mexican Spanish Community ...... 16 2.1 Introduction ...... 16 2.2 Historical Background...... 16 2.3 Characteristics of New Mexican Spanish...... 31 2.4 Linguistic Effects of Contact with English ...... 36 Chapter Three: Prosody ...... 48 3.1 Introduction ...... 48 3.2 What is prosody? ...... 48 3.3 The Autosegmental-Metrical (AM) Model of Intonational Phonology ...... 51 3.4 Spanish Prosody ...... 56 3.5 Prosody, contact, and change ...... 62 3.6 Peak Alignment ...... 66 3.6.1 Peak Alignment Variation in Contact Varieties of Spanish ...... 70 3.6.2 Spanish-English Alignment ...... 74 3.7 Rhythm ...... 78 3.7.1 Rhythm in Spanish-English Contact Situations...... 86 3.8 Pitch Range and Intensity ...... 90 3.9 Conclusion ...... 96 Chapter Four: Methodology ...... 98 4.1 Introduction ...... 98 4.2 History of the NMCOSS ...... 98 4.2.1 Subset of NMCOSS for current study ...... 102 4.3 Independent Social Variables ...... 106 4.3.1 Social Variables Hypotheses ...... 110 4.4 Data Analysis ...... 111 4.4.1 Recording and Digitization ...... 111 4.5 PVI Calculation ...... 112

4.5.1 Segmentation Criteria for Vowels ...... 114 4.5.2 PVI: Pitch and Intensity ...... 117 4.6 Peak Alignment ...... 120 4.6.1 Peak Alignment Measurement ...... 124 4.6.2 Independent Linguistic Variables in Peak Alignment Analysis ...... 127 4.6.3 Alignment Hypothesis ...... 131 Chapter Five: Results ...... 132 5.1 Peak Alignment ...... 132 5.1.1 Mixed Effects Linear Regression ...... 143 5.1.2 Social Variables ...... 157 5.1.3 Peak Alignment Results Summary ...... 164 5.2 Durational PVI ...... 164 5.2.1 Regression Analysis ...... 169 5.2.2. Non-significant Social Variables ...... 173 5.2.3 Durational PVI Results Summary ...... 186 5.3 Pitch and Intensity PVI ...... 187 5.3.1 Linear Regression Results: Pitch PVI ...... 193 5.3.2 Linear Regression Results: Intensity PVI ...... 200 5.3.3 Pitch and Intensity PVI: Non-significant Social Variables ...... 203 5.3.4 Pitch and Intensity PVI Results Summary ...... 211 Chapter Six: Discussion and Conclusion ...... 213 6.1 Introduction ...... 213 6.2 Research Questions ...... 214 6.2.1 Peak Alignment Discussion ...... 216 6.2.2 Rhythmic Timing Discussion ...... 219 6.2.3 Pitch PVI Discussion ...... 220 6.2.4 Intensity PVI Discussion ...... 224 6.2.5 Prosodic Hierarchy ...... 227 6.3 Null hypothesis ...... 230 6.4 Future Research ...... 235 6.5 Limitations ...... 241 6.6 Conclusion ...... 242

Appendix A. Speaker PVI Results ...... 246 Appendix B. Speaker Alignment Results ...... 248 Appendix C. Peak Alignment Linear Regression Random Effects ...... 250 References ...... 266

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List of Figures

Figure 1. Schema of L+>H* pitch accent. The shaded area represents ...... 52 Figure 2. The schematic for L* displays a low level that is at the bottom of the speaker’s f0 range for the phrase. The schematics for the L% boundary tones are realized as a low plateau or falling tone at the minimum of the speaker’s f0 range (adapted from Estebas-Vilaplana & Prieto 2010:19-20)...... 58 Figure 3. Late peak alignment in pre-nuclear position on the word funciona, within the utterance entiendo perfectamente como funciona todo ‘I understand perfectly how everything works’ (Bittar & Van Buren 2017) ...... 69 Figure 4. The English word ‘electricity’ spoken in isolation, demonstrating the high variability in duration across successive vocalic segments (i.e. in a stress-timed language)...... 79 Figure 5. The Spanish word electricidad ‘electricity’ spoken in isolation, demonstrating the low amount of variability in duration across successive vocalic segments (i.e. in a syllable-timed language)...... 80 Figure 6. Schemas of two realizations of a similar pitch contour produced with different ranges...... 90 Figure 7. Geographic sectors and locations targeted for the NMCOSS (Bills & Vigil .. 100 Figure 8. Map of New Mexico with Isogloss Bundle (adapted from Bills & Vigil ...... 103 Figure 9. Location where speakers in the NMCOSS subsample grew up, distinguished105 Figure 10. Measuring points at the f0 curve of the pre-nuclear rising pitch accent. (B= 124 Figure 11. Example of the peak alignment measurement. If the pitch peaks in the post- ...... 126 Figure 12. TextGrid from Interview 81 which shows the point representing the peak f0 within the tonic and post-tonic syllable of the word mismo ‘same’ in the phrase y al mismo tiempo ‘and at the same time’. Note that the alignment value is also added. The alignment value of 134.8 means that the f0 peak occurs after the offset of the stressed syllable, specifically after a temporal delay corresponding to 34.8% of the duration of the voiced portion of the stressed syllable (here, the /mis/ of mismo ‘same’)...... 127 Figure 13. Declarative phrase mi hermana se quedó con todo ‘my sister was left with everything’ with post-tonic aligned peak in hermana ‘sister’. (Interview 44, 73-year- old female from Albuquerque) ...... 133 Figure 14. Histogram of alignment score for all tokens in the data...... 136 Figure 15. TextGrid with alignment score point tier, from Interview 1 ...... 137 Figure 16. TextGrid with alignment score point tier demonstrating early alignment, from Interview 2...... 138 Figure 17. TextGrid for the phrase Tenía un cuarto arriba en esa parte del techo ‘He had a room up there in that part of the roof’ from Interview 2. Notice that two tokens in this phrase have late alignment...... 139 Figure 18. Histogram of alignment score for (C)V tonic and voiced tonic and post-tonic tokens in the data...... 140

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Figure 19. Example of a low alignment score in an open and voiced tonic syllable in the phrase Él habla más en inglés también ‘He speaks more in English, too.” (Interview 9, 29-year-old female)...... 141 Figure 20. Box plot for Alignment Score by Syllable Structure...... 147 Figure 21. Scatter plot of data distributed by Number of Intervening Unstressed Syllables...... 148 Figure 22. Box plot of alignment score distribution by Word Class ...... 149 Figure 23. Box plot of alignment score distribution by Stress Position ...... 151 Figure 24. Box plot of alignment score distribution by Phrase Position ...... 153 Figure 25. Scatter plot of token alignment scores by population in log values...... 161 Figure 26. Scatter plots for the remainder of the continuous social variables: Years of Education, Years of Spanish Education, Age Learned English, Age Learned Spanish, Spanish Language Use, and Wealth...... 163 Figure 27. Histogram of PVI scores for all tokens in the data...... 166 Figure 28. Box plot of PVI values in data set ...... 167 Figure 29. Example of high variability in successive vowels, Participant 232, 36-year-old male from Chimayo...... 168 Figure 30. Interaction plot displaying mean PVI scores for females and males depending on years of education ...... 171 Figure 31. Interaction plot displaying mean PVI scores for females and males depending on wealth...... 173 Figure 32. Box plot of PVI distribution by age group...... 174 Figure 33. Bar plot of PVI distribution by age group...... 175 Figure 34. Scatter plot of PVI results by age ...... 176 Figure 35. Individual mean PVI scores plotted by age. The red line is the regression line. The blue line is the LOWESS (Locally Weighted Scatterplot Smoothing) line. .... 177 Figure 36. Box plot of PVI distribution by gender...... 178 Figure 37. Box plot of PVI distributions by Sector ...... 182 Figure 38. Geographic sectors segmented by Bills and Vigil (2008:23)...... 183 Figure 39. Histogram of PVI distribution of Mean Pitch (a), Maximum Pitch (b), Pitch at Vowel Midpoint (c), and Mean Intensity (d) for all tokens in the data...... 190 Figure 40. Box plot distributions of dependent variables...... 191 Figure 41. Box plots of PVI distributions by age group for Mean Pitch PVI, Maximum Pitch PVI, and Pitch at the Vowel Midpoint PVI...... 196 Figure 42. Scatter plots of PVI distributions by Wealth...... 199 Figure 43. Scatter plot of mean Intensity PVI distributions by Spanish Language Use . 202 Figure 44. Box plot of PVI distributions by age group for mean Intensity PVI...... 206 Figure 45. Scatter plots for Years of Education and Age Learned English by mean intensity PVI...... 207 Figure 46. Scatter plot for Age Learned English by mean pitch PVI, ...... 208 Figure 47. Scatter plot of mean Intensity PVI by Wealth...... 211 Figure 48. Speaker mean alignment scores plotted against speaker mean durational .... 229

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Figure 49. Example of salient final post-tonic lengthening and sustained H% boundary tone in the declarative phrase que no le crece yerba ‘that herbs wouldn’t grow’. This example is from Interview 32, a 34-year-old male speaker from Albuquerque, NM. Note that ‘F’ in tier 2 marks the vowels in the final foot… ...... 237 Figure 50. Example of salient final post-tonic lengthening and sustained H% boundary tone in the phrase Antonio Lopez. The example is from Interview 145, a 50-year-old male speaker from Pecos, NM...... 238 Figure 51. Example of salient final post-tonic lengthening and sustained H% boundary tone in a declarative utterance, pues esta la conocí en un baile ‘Well I met this one at a dance’. Interview 214, 76-year-old male speaker from Ojo Feliz, NM...... 238 Figure 52. Example of salient final post-tonic lengthening and sustained M% boundary tone in the declarative utterance de demasiado importancia ‘of utmost importance’. Interview 118, 59-year-old male speaker from La Loma, NM...... 239 Figure 53. Example of a rise in the nuclear pitch-aligned syllable and followed by a sharp fall into a lengthened post-tonic syllable in the declarative utterance Me acuerdo una vez que tiramos toda la tierra a la azotea ‘I remember one time we through all the dirt at the roof’. Interview 118, 59-year-old male speaker from La Loma, NM. .... 239

List of Tables

Table 1. Overview of pitch accents and boundary tones found in pre-nuclear and nuclear ...... 60 Table 2. Social variables and their factors...... 107 Table 3. Participant socio-demographic and language use information...... 108 Table 4. Independent linguistic variables and their factors ...... 129 Table 5. Overall distribution of pre-nuclear f0 peaks...... 133 Table 6. Tonic and post-tonic alignment percentages as reported for different varieties of Spanish ...... 134 Table 7. Overall distribution of pre-nuclear f0 peaks for open tonic syllables and voiced segments in the tonic and post-tonic syllables...... 139 Table 8. Rbrul results for significant predictor variables on Alignment Score ...... 145 Table 9. Mean alignment score by variable Word Class ...... 149 Table 10. Mean alignment score by variable Stress Position ...... 150 Table 11. Mean alignment score by variable Stress Position ...... 153 Table 12. Rbrul results for significant predictor variables on Alignment Score when tokens with voiceless segments and closed tonic syllables are excluded ...... 155 Table 13. Mean alignment score for discrete social variables ...... 158 Table 14. Output of Wilcoxon rank sum tests for the variable Age Group ...... 159 Table 15. Mean PVI scores in Carter (2005:70), White and Mattys (2007:508), and the current dissertation study ...... 166 Table 16. Rbrul results for significant predictor variables on Alignment Score...... 170 Table 17. Mean PVI scores for females and males by Years of Education...... 171 Table 18. PVI means for females and males distributed by years of education...... 172 Table 19. Statistical Information for speakers broken down by age group ...... 174 Table 20. Statistical Information for speakers broken down by Gender ...... 178 Table 21. Mean PVI scores of males and females when broken down by age group. ... 179 Table 22. Mean PVI scores for additional social variables ...... 180 Table 23. Mean, median, maximum, and standard deviation of different PVI...... 189 Table 24. Rbrul results for significant predictor variables on Pitch PVI...... 194 Table 25. Mean PVI pitch variables broken down by age group...... 195 Table 26. K-Sample Fisher-Pitman Permutation Tests showing significant difference . 196 Table 27. Multiple Comparisons table for Wilcoxon rank sum tests for Age Group ..... 197 Table 28. Mean PVI scores by wealth; the higher the value, the higher the wealth of .. 198 Table 29. Rbrul results for the significant predictor variable on mean intensity PVI. ... 201 Table 30. Mean PVI scores for Spanish Language Use...... 202 Table 31. Mean PVI scores for additional social variables ...... 203 Table 32. Socio-demographic information and raw PVI scores for participants who .... 208

xvi

Chapter One: Introduction

The data this study is based on come from the New Mexico-Spanish Colorado Survey

(NMCOSS) which consists of sociolinguistic interviews with New Mexican Spanish speakers. Interviews begin with a string of questions intended to elicit demographic information and information pertaining to language usage. A pattern emerged while listening to responses to questions such as, “What language do you speak at home,

Spanish or English?”, and, “What language do you prefer to watch television in or listen to on the radio? English or Spanish?” Speaker after speaker, young and old, repeated the answer, “Casi nomás inglés” ‘practically just English’. Sometimes this was said with the regional variant cuasi, hence the title of this dissertation.

The crossroads of English, Spanish, and indigenous languages in the Southwest have had repercussions not only in communities and livelihoods, but also in language, the focus of the current study. The linguistic consequences of the shift from purely Spanish- speaking households in the early 1900s to predominantly English-speaking households in the late 1990s in New Mexico are ripe for investigation, particularly in the domain of prosody. The term prosody refers to the suprasegmental characteristics of melody and timing (e.g. intonational and rhythmic properties of speech) and contributes to the perception of a distinct dialect, language, or foreign accent. Anecdotally, the prosody of

New Mexican Spanish has a unique melody (Hills 1906, Lipski 2011), although a rigorous acoustic analysis has heretofore not been undertaken (although see Benevento

2017 for a study on the acoustic correlates of prominence in New Mexican Spanish). It is known that prosody, like other domains of language, is susceptible to change in contact situations, particularly if the social settings are ripe for it (Thomason & Kaufman 1988).

However, the particulars of how the various parameters of prosody change remain largely unknown.

The goal of this dissertation is to analyze how apparent-time data consisting of conversational speech in the NMCOSS can be used to investigate prosodic change in a long-term language contact setting using “Traditional New Mexican Spanish” as a specific case study. The term “traditional” to describe the Spanish of descendants of pre-

20th century settlers into the Southwest region was first used by Lope Blanch (1987) and was then adopted by Bills and Vigil (1999, 2008). I find this term provides a useful distinction between the Spanish that has been spoken in northern New Mexico and southern Colorado for over one hundred years and the Spanish that has been introduced into the region more recently via immigration. Therefore, this study adopts the label

“Traditional New Mexican Spanish”, or simply “New Mexican Spanish” (NMS) to refer to the Spanish brought into New Mexico by pre-twentieth century settlers. Furthermore, using Bills and Vigil’s (2008:7) conventions, the label “Border Spanish” refers to

Spanish brought into New Mexico by twentieth century immigration, and “Mexican

Spanish” refers to Spanish spoken in present-day Mexico.

This study aims (1) to understand NMS in its sociolinguistic context, which involves investigating its history of contact primarily with English, and (2) to provide an empirical analysis of prosodic variables in NMS that constitute points of contrast between

Spanish and English: f0 alignment, durational timing (also called rhythmic timing), and pitch variability. The prosodic analysis is framed under the Autosegemental Metrical

(AM) model of intonation theory (Pierrehumbert 1980, Ladd 1996). The prosody of NMS is perceptually distinct from other contemporary varieties of Spanish; how do these

2 prosodic patterns arise and what features make this variety unique? I hypothesize that, at least in part, transfer of English-like patterns happened during this period of contact between Spanish and English. The NMCOSS corpus is suitable for testing this hypothesis because participants therein have birth dates that span approximately one hundred years

(1897-1978), precisely the period that saw the change from a Hispanic majority to a

Hispanic minority in New Mexico concomitant with an increase in English-Spanish societal bilingualism.

The apparent-time construct involves synchronically comparing speakers of different ages and inferring the state of ongoing language change based on differences across ages (Meyerhoff 2011). Comparing prosodic variation across speakers in the

NMCOSS corpus allows us to trace the unfolding and social trajectory of this change.

Furthermore, the prosodic variables analyzed in this study (f0 peak alignment, durational timing, and pitch variability) differ between Spanish and English and therefore provide a quantitative point of comparison. A lack of significant apparent-time differences would indicate that contact with English has not been a factor in the development of unique prosodic patterns in NMS. Differences across the generations, on the other hand, would generally be interpreted as indicative of ongoing change. Results would elucidate which prosodic features are more susceptible to borrowing and how sociodemographic and language use factors contribute to contact-induced change in a long-term contact setting.

NMS is a variety of Spanish with a unique history of contact and over three hundred years of isolation from other Spanish-speaking communities. Language-internal and language-external influences likely combine to play a role in the unique prosodic patterns heard in NMS. Language-external influences would come from contact with

3 indigenous languages in the region (e.g. Nahuatl in Mexico and indigenous languages of

NM) or with English. According to Bills and Vigil (2008:154), NMS speakers historically had little contact with speakers of indigenous languages in NM, e.g. Pueblo languages, due to rigid social barriers. However, given the close settlement patterns where Spanish settlers built their early missions along the edges of Pueblo villages, there was likely more interaction than commonly assumed (Nostrand 1992:51). Another example of contact between Spanish settlers and indigenous people was the frequent occurrence of captured or ransomed native people from nomadic tribes (e.g. Apaches and

Navajo), called genízaros, taken for cheap labor in colonial New Mexico (Weber

1992:307). The genízaros may have been a source of early contact effects, although the prevailing claim in the literature on NMS is that influence from indigenous languages on

NMS is scarce (Bills & Vigil 2008:154). However, it is of note that a unique NMS intonation has been reported since the early twentieth century (Hills 1906).

Before Spanish speakers settled in NM, they interacted chiefly with Nahuatl speakers in the New World for over one hundred years. This led to a certain degree of influence, most noticeably in lexical items (Bills & Vigil 2008:93). However, it is unlikely that the intonational patterns that differ between New Mexican and Mexican

Spanish (the Spanish variety with the closest geographic and historical proximity to

NMS) have been influenced by Nahuatl, since Nahuatl-influenced patterns in NMS would also be present in modern-day Mexican Spanish. Another possible candidate for unique prosodic patterns found in present-day NMS is English. Spanish-English bilingualism increased in NM throughout the 19th and 20th centuries, resulting in sustained long-term contact with English. To illustrate, in 1890, 70% of the New Mexico

4 population could not speak English; twenty years later, in 1910, only 32.5% of the population could not speak English (Fernández-Gibert 2010:48). Public education, enacted in 1891, was developed with English as the language of instruction (Fernández-

Gibert 2010:56), although English instruction did not reach all rural areas until decades into the 20th century (Gonzales Velásquez 1995). Since the Spanish-English language contact situation in NM unfolded mainly over the twentieth century, with WWII a major turning point leading to a majority Anglo population (Bills & Vigil 1999), it is possible to indirectly analyze how quickly transfer happened or whether unique intonational patterns in NMS were already present when New Mexico was largely monolingual in Spanish (i.e. turn of the 19th century). In the latter case, changes would be due to language-internal pressure (Cruttenden 1986, Britain 1992), rather than to transfer from L2 English to L1

Spanish.

The analysis of NMS prosody in this dissertation is based on a subsample (n=60) of native New Mexican Spanish speakers from the NMCOSS corpus who were between the ages of 18 (born 1977) and 95 (born 1898) at the time of the recording, and who were selected based on an even distribution of age and gender. There is almost a century difference between the speakers’ birth years in this subsample, which provides the advantage of analyzing apparent-time changes through a period of increasing English presence. This corpus represents different degrees of bilingual proficiency, although all speakers learned Spanish in early childhood, and the data provide clues to changes in intonation in this long-term contact situation.

Specifically examined in this study is f0 alignment in a specific pitch accent pattern in declarative broad focus statements, in pre-nuclear (i.e. non-phrase final)

5 position. ‘Pitch accent’ refers to the fact that in many languages, including both English and Spanish, speakers cause a subset of words in an utterance to stand out from the surrounding words. This is achieved by producing distinctive patterns of pitch movement on those words. These patterns can be analyzed as being associated with the stressed syllables of each word. The typical broad focus pre-nuclear pitch accent in declaratives in

Spanish is characterized by a different pitch pattern than that of English, as described in depth in Chapter 3. The pitch accent analysis is informed by an investigation into the phonetic alignment of the maximum f0 (the acoustic correlate of pitch) with relation to the end of the tonic syllable. In addition to this feature, the present study examines pitch variability and durational timing to assess rhythmic patterns. Pitch variability refers to the changes in pitch across successive vowels and is meant to be a local measure of pitch range, which refers to the difference between the highest and lowest point in a speaker’s f0 movements over utterances and to various f0 oscillations in between (Hirschberg &

Pierrehumbert 1986:137). Durational or rhythmic timing refers to the differences in syllable or vowel duration across successive syllables, which gets at the perceived difference between more stress-timed languages (e.g. English, with larger differences in length) and more syllable-timed languages (e.g. Spanish, with smaller differences between syllable lengths), keeping in mind that timing is better viewed as a relative continuum (Dauer 1983). The rhythmic metric used in this study to measure durational timing (as well as pitch variability) is the Pairwise Variability Index or PVI, which measures differences in duration (or pitch) between consecutive stressed and unstressed syllables (Low 1998, Low & Grabe 1995, Low, Grabe, & Nolan 2000, Grabe & Low

2002). Furthermore, this study measures variability in intensity, which is known to be an

6 additional acoustic cue to convey prominence in Spanish (Navarro Tomás 1964, Ortega-

Llebaria 2006, Ortega-Llebaria & Prieto 2007b). Intensity is measured in order to see whether this variable plays a greater or lesser role in signaling prominence as other acoustic correlates of prominence (i.e. pitch and duration) become more or less variable

(see Nokes & Hay 2012) and is included in order to provide a more comprehensive picture of prosodic change through time.

The variables chosen for this study have been demonstrated to be susceptible to transfer in contact situations, including Spanish-English settings (for peak alignment,

Colantoni 2011, O’Rourke 2005, Elordieta 2003, Michnowicz & Barnes 2013; for pitch range Enzinna 2015, Kelm 1995; for rhythm, Thomas & Ericson 2007, Carter 2005,

Enzinna 2015, Robles-Puente 2014, Nokes & Hay 2012). The variables chosen differ between Spanish and English and therefore allow for an empirical analysis of English influence on Spanish prosody in New Mexico.

The performance of bilinguals in such long-term language contact settings has been understudied, as have the consequences of long-term contact on phonology in general (Bullock 2009:167). Furthermore, the majority of studies on contact-induced phonological change have focused on segmental rather than suprasegmental features. In addition, while studies on intonation in Spanish contact varieties are expanding, few focus on the influence of English intonation on Spanish, with exceptions such as Alvord

(2006), who looks at Cuban Spanish interrogative patterns in Miami, Robles-Puente

(2014), who looks at Mexican Spanish rhythm and intonation patterns in Los Angeles, and Carter (2005) and Carter and Wolford (2016) who look at Mexican Spanish and

English rhythm in Texas. These studies examine patterns across generations of speakers

7 in Spanish communities in the U.S. and find evidence of English influence on Spanish intonational patterns. The present study therefore seeks to add to the understanding of consequences of long-standing contact on the borrowing of prosodic variables, taking into account the social status of the languages in the community. Specifically for New

Mexico, this study is interested in how the dominant language (English, the language of the socially prestigious group in New Mexico) has influenced the subordinate language

(Spanish, the language of the socio-politically less powerful group) (see Thomason

2001).

1.1. Research Questions and Hypotheses

Given the increase of English dominance in New Mexico throughout the 20th century, I expect to find apparent-time differences in peak alignment, pitch variability, and durational timing in NMS prosody, with variables becoming more English-like across the generations. If there is demonstrable change in NMS on these prosodic variables, we can ask: Is this due to the new political and socioeconomic conditions of the 20th century which intensified Spanish-English contact and accelerated shift toward English, such as

New Mexico’s statehood in 1912, World War II and the ensuing Cold War federal investment in the state (Sánchez, Spude, & Gomez 2013)? Using the apparent-time construct on a sample of 60 speakers from the NMCOSS corpus, we can infer whether change has occurred or whether NMS has essentially remained stable on these variables.

In particular, this study aims to answer the following questions:

1. Has Spanish remained stable in New Mexico over the twentieth century in terms of prosody, or have prosodic patterns in NMS been influenced by prolonged contact with

English in the form of Spanish-English bilingualism? In particular,

(a) How do the patterns in NMS compare to reported patterns in monolingual

varieties of Spanish, in particular Peninsular (Face 1999, Face & Prieto 2007,

Prieto, Van Santen, & Hirschberg 1995, Estebas-Vilaplana & Prieto 2010, among

others) and contemporary Mexican Spanish (de-la-Mota, Butragueño & Prieto

2010)?

(b) How do patterns in older speakers compare to patterns in younger speakers in

the NMCOSS corpus, with age measured as a continuous variable?

(operationalized as variability across successive vowel segments), do pitch and

intensity change in parallel as a compensation strategy? That is, as one acoustic

cue to prominence (pitch, duration, or intensity) becomes more or less variable,

do other acoustic parameters change in tandem?

(d) Along with (c), is there a prosodic hierarchy in terms of the susceptibility of

different prosodic variables to change? That is, are some prosodic features more

likely to change than others?

2. If NMS does exhibit change in apparent-time, what socio-demographic and language use factors correlate with whether NMS speakers exhibit more English-like Spanish intonational and prosodic patterns? In other words, what are the social driving forces behind intonational change? In particular,

(a) How do prosodic patterns correlate with socioeconomic status operationalized

as wealth and years of education?

(b) How does English input in childhood and age of Spanish and English

acquisition correlate with prosodic change?

influence from English?

(d) Is there regional variation operationalized as differences across the four

delineated regions of New Mexico? Furthermore, is there a correlation between

prosodic change and population, in that the more urban areas have had more

influence from English, possibly due to looser social networks?

3. Alternatively, if NMS does not exhibit apparent-time change in prosodic patterns, what is it about the language situation in NM that has inhibited prosodic change, which is known to be highly susceptible to influence in contact situations (see Matras 2007)?

In order to address the questions outlined above, this study measures alignment, vowel duration, pitch, and intensity and enters these as dependent variables in separate mixed-effects regression analyses in order to determine the relative effects of independent variables, including age as a continuous variable, gender, and years of formal education. The sociolinguistic component in this study is motivated by research which finds that in contact situations, innovation and change in the native language can be affected by the second language depending on the amount of and length of exposure to the second language (e.g. Silva-Corvalán 1994). The speech community considered in this study, speakers of traditional New Mexican Spanish, have roots in a Spanish variety

10 that has been in the region for well over one hundred years and throughout that time speakers have experienced the increasing presence and societal influence of English.

Given the findings on differences in English and Spanish prosodic patterns and studies on Spanish in contact with English and other languages which will be described in depth in Chapter 3, I hypothesize and predict the following in response to the research questions posed above:

1. Peak alignment patterns in NMS are hypothesized to have been influenced by prolonged contact with English. In particular,

(a) Peak alignment patterns in NMS are expected to show characteristics of

English peak alignment patterns. Specifically, in pre-nuclear broad focus

declarative pitch accented syllables, NMS is expected to exhibit f0 peak

alignment within the tonic syllable, similar to English (e.g. Silverman &

Pierrehumbert 1990) and contact varieties of Spanish (e.g. O’Rourke 2005,

Colantoni & Gurlekian 2004, Michnowicz & Barnes 2013, Barnes & Michnowicz

2013), whereas central Mexican Spanish and non-contact varieties of Spanish

exhibit delayed peak alignment (Prieto & Roseano 2010; de-la-Mota et al. 2010).

(b) Peak alignment is hypothesized to be more similar to monolingual varieties of

Spanish the older the speaker. In other words, the younger the speaker, the more

likely he or she is to exhibit early peak alignment.

2. Rhythmic timing in NMS is hypothesized to have been influenced by prolonged contact with English.

(a) Spanish has been characterized as a syllable-timed language because the

difference in duration between stressed and unstressed syllables is less extreme in

Spanish than in English, which has been characterized as a stress-timed language.

Although the distinction is controversial and better described as a continuum,

rhythmic timing has been shown to change in contact situations, including that of

Spanish-English contact (Carter & Wolford 2016, Robles-Puente 2014, Enzinna

2015). I hypothesize that NMS has become more stress-timed throughout the

twentieth century; in concrete terms, this means that using the PVI formula, where

1=absolute difference in duration across successive (vocalic) segments and 0=no

difference in duration across successive (vocalic) segments, mean PVI values in

Spanish increase the younger speakers are.

3. Pitch range in NMS is hypothesized to have been influenced by prolonged contact with

English.

(a) In NMS, pitch variability, a local measure of pitch range, is expected to be

more characteristic of English. English is said to exhibit a wider pitch range than

Spanish (Kelm 1995, Enzinna 2015, Navarro Tomás 1944, Stockwell & Bowen

1965, Cruttenden 1986). Therefore, pitch variability is hypothesized to increase

the younger the speaker. Pitch variability is operationalized as variability in mean

pitch across successive vowels using the PVI formula (Low & Grabe 1995).

Furthermore, as durational variability increases or decreases, pitch and intensity

are expected to change inversely, though speakers may make use of pitch and

intensity to a different extent (e.g. Nokes & Hay 2012).

4. Sociodemographic, language use, and attitudinal factors are hypothesized to correlate with whether NMS speakers exhibit English-influenced Spanish intonational and prosodic patterns. In particular,

(a) According to Bills & Vigil (1999), speakers in NM who have had more years

of education are also more integrated into North American culture. Therefore, it is

expected that speakers with more years of formal education exhibit a higher

amount of borrowing from English, due to greater English input and integration

into Anglo culture and less reinforcement of Spanish-monolingual patterns.

(b) Simultaneous bilinguals (i.e. bilinguals who acquired Spanish and English at

roughly the same time) are more likely than sequential bilinguals (i.e. bilinguals

who acquired Spanish first and then subsequently English in school) to use

English-influenced intonational patterns in their Spanish, due to more input in

English. Furthermore, sequential bilinguals who acquired English first and

Spanish second should also exhibit more English-like patterns than the

simultaneous bilinguals due to fewer years of Spanish input in childhood.

friends, the less English prosodic influence will be exhibited in their speech, again

due to the reinforcement of non-contact Spanish prosody.

Alternatively, if there is no apparent-time effect in prosodic change, then it can be assumed that prosody has remained relatively stable in NMS throughout the 20th century.

In this case, the unique prosodic patterns that make NMS stand out as a distinct variety could either be due to (1) features that were already in place pre-widespread English bilingualism, in which case the oldest speakers will exhibit the features, or (2) unique prosodic features that have indeed developed in NMS, but are features which are not considered quantitatively in this study. In the former case, we can assume that NMS has remained relatively impervious to English influence, a result which has been found in

13 several studies of NMS (Torres Cacoullos & Travis 2011, Benevento & Dietrich 2015,

Balukas & Koops 2015). In this case, speakers exposed to two prosodic systems would be shown to be able to maintain a monolingual-like Spanish phonology. In the second possibility, the influence of English cannot be inferred either way, but would require further research. Unique prosodic features not attributed to English could be a result of isolation from other Spanish-speaking communities (i.e. internal cause of change).

Furthermore, Traditional New Mexican Spanish communities are characterized by strong ethnic boundaries and tend to be clustered in rural and poor communities (Solé 1980,

1990). Residents in such communities tend to be part of tight-knit social networks, which are known to reinforce vernacular patterns and resist change from external pressures

(Milroy 1987).

The literature on language-internal and external causes of prosodic change is scarce. This study contributes to the literature on prosodic change in long-term contact settings, in particular on the use of apparent-time data to elucidate such findings.

Furthermore, this study adds to the literature on prosodic variation in Spanish, including

Spanish in the United States. Results on the New Mexico speech community are informative regarding how sociolinguistic factors shape the prosodic system of a minority language community experiencing long-term bilingualism. Thus, this dissertation study contributes to the fields of sociophonetics, language contact, and bilingualism.

This dissertation is structured as follows. Chapter 2 discusses the history of New

Mexican Spanish, and gives an overview of its linguistic characteristics. This chapter also describes previous studies which focus on Spanish-English bilingualism in New Mexico, and provides a description of the language and dialect shift phenomena which have been

14 ongoing in New Mexico. This provides context for the current study and findings.

Chapter 3 discusses the Autosegmental-Metrical model of intonation in order to provide a framework with which to describe NMS prosody. This chapter also reviews the literature of prosody in contact and describes in depth the variables chosen for this study, as well as cases where they have been found to change in Spanish contact settings. Chapter 4 describes the methodology used in this study, and Chapter 5 provides the findings and interprets them in quantitative terms. Chapter 6 discusses the results which find little evidence for contact-induced influence from English and ties the findings together with a qualitative interpretation. This chapter also discusses a salient prosodic feature heard in the corpus sample but was not measured due to its finding post-hoc, but should be considered in further research. Finally, this chapter considers how the social characteristics of the New Mexican Spanish speech community has been a factor in the resistance of NMS to structural influence from English.

Chapter Two: Historical and Linguistic Background of the New Mexican Spanish

Community

2.1 Introduction

Any discussion of language contact must consider the socio-historical forces that have shaped the speech communities in question. This chapter provides details on the traditional Spanish-speaking population of New Mexico and gives historical information on how Spanish and English came to be spoken in the region. The main goal of this chapter is to review the literature regarding what previous authors have said about the influence of English as an explanatory variable in understanding the history of NMS, setting the stage for the present dissertation study. I begin with an overview of the history of Spanish in New Mexico, including its social evolution from the dominant majority language of the state to a minority language facing fewer and fewer domains where it is used. This discussion situates the Spanish-English bilingualism within the context of NM history, and what predictions the specific unfolding of bilingualism and language shift make for the likelihood of English influence on Spanish at the prosodic level. I then describe the linguistic characteristics that make Traditional New Mexican Spanish a unique dialect of Spanish, and follow by describing linguistic effects of English on NMS, showing how prosodic transfer is possible via borrowing into NMS.

2.2 Historical Background

In order to understand the present-day situation of New Mexican Spanish, it is important to gain an understanding of this variety’s historical roots. Traditional Spanish in New

Mexico represents “the oldest continually spoken variety of Spanish anywhere in the

Americas that has not been updated by more recent immigration from Spain or neighboring countries” (Lipski 2008:193). According to Bills and Vigil (1999), this variety, which had already been developing and mixing with indigenous languages in the

Americas for a hundred years, was brought into New Mexico in 1598 with Juan de

Oñate’s expedition. Oñate established the first permanent Hispanic settlement in the territory that today comprises the United States in San Juan, in what is now northern New

Mexico. According to Nostrand (1992:29), the original group of settlers were of mixed population, with the majority having been born in Spain, and most of the others having been born in New Spain. From the time Spanish was brought into New Mexico with

Oñate to now, the history of NMS speakers has been intertwined with that of Pueblo

Indians, nomadic Indians, Anglos, and Mexican Americans in the region (Nostrand

1992). While we will see that English is by no means the only language which could have influenced NMS structurally, it represents the language with which NMS has had the most intense contact in terms of the number of bilingual speakers and fluency level of speakers (Thomason 2001:69).

According to Sanz and Villa (2011:437), the one hundred years or so that Spanish was in the New World before making its arrival into New Mexico led to dialect mixture and leveling that resulted in a distinct dialect. The indigenous language Nahuatl made its mark on New World Spanish during the 16th and 17th centuries, the traces of which are still present in NMS, for example in the lexical items mecate ‘shoelace’ and guajolote

‘turkey’ (Bills & Vigil 2008:112-119). For centuries after this variety of Spanish arrived in New Mexico, the Spanish-speaking community was relatively isolated from other varieties of Spanish as there was little contact between the settlements in northern New

Mexico and the major cities of what is now Mexico. This led to both the retention of features that changed elsewhere in the Spanish-speaking world (i.e. words such as asina

‘like that’, instead of the standard así), and to innovations unique to NMS (e.g. lexical items such as ratón volador ‘bat’, instead of the standard murcielago) (Bills & Vigil

2008:15). During this time, New Mexican Spanish speakers interacted with two different

Native American groups, the Pueblo Indians and the nomadic Indian tribes, which included the Navajo, Apache, Utes, and Comanches (Nostrand 1992, Bills & Vigil

2008:153-154). The area occupied by the original Spanish missions followed the same path as local Pueblo villages, and the population of early New Mexicans was distributed mostly along the valley of the Rio Grande and the tributaries that flowed off the Rio, which is where the Pueblo Indians were located (Nostrand 1992:36). Because of this, there was considerable contact between the Pueblo Indians and New Mexican Hispanics.

However, Bills and Vigil (2008:154) claim that there is a lack of influence from Pueblo languages on Spanish, possibly due to the variety of Pueblo languages spoken, the rapid decline of the Pueblo population, and the “erect rigid barriers around their culture” that maintained a distance between themselves and the Spanish speakers. Furthermore, it was more common for Pueblo Indians to become bilingual in Spanish rather than the other way around. However, this could lead to a situation where Pueblo Indians, being L2 speakers of Spanish, impose features from their L1 on the Spanish spoken in the region.

Indeed, the assumption that native languages have not influenced Spanish is based on observations of lexical items, and there are no analyses of structural influence. In addition, speakers of indigenous languages in the region greatly outnumbered NMS

18 speakers until the mid-1700s (Bills & Vigil 2008:154, citing Gutierrez 1991:167). The picture of Pueblo languages’ influence on NMS is therefore incomplete.

Even though relations with the nomadic tribes were hostile, this also provides a possible source of contact effects in NMS due to the practice of capturing children and women from these tribes who came to serve in New Mexican households. These captured nomadic Indians were known as genízaros, and many of them were women whose mixed children assimilated into the Spanish population (Nostrand 1994:4,20, 44). The practice of capturing genízaros represents an intimate relationship between speakers of Native

American languages in the region and NMS speakers, which may have led to linguistic influence from nomadic Native Americans. However, Nostrand (1992:44) claims that the genízaros became Spanish-speaking Christians and many formed their own settlements as barriers to hostile nomadic aggressions. Furthermore, Bills and Vigil (2008) claim that linguistic influence from nomadic tribes was unlikely due to the social esteem placed on

Spanish but not on Native American languages. The extent of indigenous language influence on NMS is therefore not well understood, but thus far little influence has been reported.

It was not until the nineteenth century that English had any real presence in New

Mexico. At the beginning of that century, New Mexico was still a colony of Spain and had a population of 60,000 Spanish speakers and few English speakers (Bills & Vigil

2008:24). Anglos (that is, “non-Indians and non-Spanish/Mexican Americans”, Nostrand

1992:4) were in such small numbers that they assimilated to Spanish culture and language, and tended to marry into Spanish families (Nostrand 1992:103). Then, Mexico gained its independence from Spain in 1821, and the Mexican government subsequently

19 opened the Santa Fe Trail that extended from New Mexico to Missouri (Nash 1994:4).

This marks the first “official” point and time of contact between Spanish and English speakers in New Mexico, as the trade route increased interactions between Mexicans and

Americans and led to an expanding population of Anglos in New Mexico, who were eager for new economic opportunities, according to Nash (1994:4). Even so, Anglo migration into New Mexico occurred at a much slower pace than elsewhere in the

Southwest and California (Sanz-Sánchez 2014:223).

Anglo soldiers entered New Mexico in 1846 during the Mexican-American War in an effort to fight and secure the Southwestern territories for the westward expansion of the United States. The Treaty of Guadalupe Hidalgo in 1848 ceded New Mexico as a territory to the United States, and with that the presence of Anglos increased, and so too did the influence of Anglos in New Mexican politics and government. Regardless, after

1850, the number of English-speaking settlers into the region increased slowly due to the isolation and remoteness of New Mexico (Nash 1994:4). The slow arrival of Anglos into the territory is exemplified by the fact that the latter half of the nineteenth century saw an increase of only 17,000 Anglos (Gonzales Velásquez 1992:21, citing Sánchez 1983). As stated previously, the Anglo presence in New Mexico was much less than in other

Southwestern states and California. For example, while in 1890 the percentage of the population over 10 unable to speak English in New Mexico amounted to 69.93%, in

California the percentage was only 0.85% (Sanz-Sánchez 2014:224). The turn of the century still saw a heavily Hispanic state, where Anglos represented only 30.1% of the population (66,073 people, although this number also includes southern Colorado)

(Nostrand 1992:118). In addition, the population of people who could not speak English

20 remained roughly the same between 1890 (n=59,778) and 1910 (n=60,239) (Fernández-

Gibert 2010:48). The low numbers of English speakers in the state and the high number of Spanish monolinguals at the turn of the century is important because it means that substantial influence from English on NMS was up to that point unlikely.

Three major events influenced the number of Anglo migrants into New Mexico, greatly increasing their presence. The first was the Santa Fe railroad, which reached New

Mexico in 1879 and connected the state with Missouri (Fernández-Gibert 2010:45). The second was the admission of New Mexico into statehood in 1912. At this time, public education was enacted in English, although schooling continued in Spanish in many rural areas well into the 1930s (Lipski 2008:203; Gonzales Velasquez 1995:427; Espinosa

1914-15:243-244). From the time of statehood forward, the use of Spanish in official domains such as politics, education, and commerce declined. Such a change in language status precipitated the shift from Spanish to English starting with English use in public domains, and led to the necessity for Spanish speakers to become bilingual in English, although.

The third and most impactful major event that changed the dynamics of language and culture in New Mexico forever was World War II. Both this war and the Cold War generated a large investment on the part of the federal government in the state and brought a wave of people into New Mexico, which also fueled urban development.

Before World War II, the population of traditional New Mexican Spanish speakers was largely confined to rural areas of northern New Mexico. According to Nash (1994:10), the changes caused by World War II essentially disrupted rural lifestyles due to the enlistment of a large number of young Hispanic men. In addition, one-third of men under

25 from northern New Mexico left during this period to find economic prosperity in the newly created defense-related jobs in the Pacific states. World War II also hastened linguistic and cultural assimilation as the Hispanic and Native American men “returned home determined to eradicate the racial inequities that had traditionally limited their social mobility" (Sánchez et al. 2013:259). Furthermore, serving in the war entailed the interaction of young Hispanic men with a large number of English speakers from different parts of the country. Some amount of linguistic assimilation must have taken place for soldiers, since Hispanic men from northern New Mexico had more exposure to

English than ever before and returned to New Mexico after that experience.

The development and jobs that sprouted from the military and scientific installments after World War II contributed to the most rapid population growth in New

Mexico. In 1950, the population of Albuquerque (New Mexico’s largest city) was

100,000; ten years later, the population had doubled due to military installations such as the building of Albuquerque's Kirtland Air Force Base in 1948 and scientific projects that were federally funded post-1940 (Nash 1994:13, Sánchez et al. 2013:300). It seems clear that an increase of that size when the population of New Mexico was relatively small comes with significant changes in social dynamics. One of the greatest changes was the relative proportion of Hispanics and Anglos; the mid-twentieth century saw the Hispanic population become an ethnic minority in New Mexico (Bills & Vigil 2008:37), although small towns and rural communities would still have been heavily Hispanic (see, for example, Hudson-Edwards & Bills 1982 on Martineztown in Albuquerque).

Albuquerque’s population grew from 35,000 people in 1940 to 201,189 in 1960, an almost six-fold increase (Sánchez et al. 2013:300). Between 1940 and 1990, the state of

New Mexico saw a change in population from 530,000 people to 1.5 million, most of which centered in the towns and cities (Nash 1994:20). In sum, the traditional characteristic of rural populations and agricultural lifestyle that had heretofore characterized the New Mexico Spanish population had changed to an urban-centered economy post-World War II.

In addition to sociodemographic changes, the generation born around World War

II saw widespread technological change which accelerated the shift from a Hispanic, largely Spanish-speaking culture to an English-based American culture. According to

Nash (1994), the technological changes with the greatest cultural significance in New

Mexico were the expansion of air travel after 1945 and the availability of television in the

1950s which standardized American popular culture. Not only did New Mexicans no longer feel as isolated, but the English language and American culture was now accessible in every living room. Furthermore, it was during this time that the use of

Spanish in schools was in many cases prohibited and often met with punishment or explicit intimidation (MacGregor-Mendoza 2000; Bernal-Enríquez 2002). Spanish- speakers experienced racial segregation and discrimination not only in schools, but in public settings. As a result of such experiences, along with the increased societal presence of English, this generation “later made the widespread parental decisions not to speak Spanish at home and to use more English with the younger generations” (Bernal-

Enríquez 2002:225). This would undoubtedly affect how much input subsequent generations receive in both Spanish and English, with a marked reduction in Spanish input.

What was the reality of Spanish-English bilingualism for New Mexican Spanish speakers, and how did the shift from a largely Spanish monolingual to a largely English monolingual population happen? Case studies of New Mexico villages and rural communities paint a picture of emerging bilingualism characterized by a change from a majority of Spanish mother-tongue speakers in 1950 to an almost-complete shift to

English by the end of the century (Bills, Hernández Chávez, & Hudson 2000, Hudson,

Hernández Chávez, & Bills 1995). Several case studies detail the language maintenance and shift situation in various small towns throughout New Mexico, which show similar generational changes in mother-tongue claiming, language proficiency, and use. Hudson-

Edwards and Bills (1982) and Kravitz (1985) report on Martineztown, an urban Hispanic barrio of Albuquerque with a majority population of residents with New Mexican heritage. Hudson-Edwards and Bills (1982) carried out a pilot survey with 61 families in

Martineztown in 1975 to gain a clearer picture of the language situation in this community. They found that 92% of the families were of Spanish heritage (Hudson-

Edwards & Bills 1982:138), demonstrating the ethnically homogenous nature of this community. This community has been characterized by a tight-knit social structure that has allowed for the maintenance of New Mexican Spanish well into the late 20th century.

For example, Hudson-Edwards and Bills (1982:140) found that almost all individuals over twenty-five claimed Spanish as their sole mother tongue (Hudson-Edwards & Bills

1982:140).

Hudson-Edwards and Bills (1982) were also interested in language proficiency and asked participants to report on their fluency in Spanish and English, with the possible ratings being "none/poor", "fair", and "good/very good". Out of 173 individuals, 53

(31%) reported being "good/very good" in both languages, a higher percentage than those who reported "good/very good" in English but "none/poor" in Spanish (n=24, 14%).

Conversely, there were 21 speakers, or 12%, who were "good/very good" in Spanish but

"none/poor" in English. In other words, the majority of participants had a fluent command in both languages or were "fair" in one language and "good/very good" in the other (n=65, 38%) (Hudson-Edwards & Bills 1982:142). These data demonstrate the prevalent bilingualism in the community in the mid-1970s. By the 1980s, however, younger speakers were experiencing increasing interactions with the urban center that led both Hudson-Edwards and Bills (1982) and Kravitz (1985:30) to conclude that language shift had begun in this community. Hudson-Edwards and Bills (1982) found that the number of speakers who reported fluency in Spanish was less than the number who reported Spanish as a mother tongue, and that furthermore, this number exceeded those who reported Spanish as the primary home language, data which represents an early indication of shift to English according to the authors.

Kravitz (1985) built on the findings of Hudson-Edwards and Bills (1982) by conducting seventy sociolinguistic interviews of Martineztown residents which focused on language attitudes, including attitudes towards English and Mexican Spanish.

According to Kravitz (1985:24), the shift towards English was evident when considering that the oldest generation of Martineztown residents used Spanish almost exclusively in all domains, the middle generation used both Spanish and English depending on the social domain, and the younger generation primarily used English in most domains, excluding the home. Furthermore, participants in Kravitz’ language attitude study considered Mexican Spanish the model for formal and educated Spanish, while

25 stigmatizing their own dialect. Formal situations in the community either called for

Mexican Spanish or English, as the Spanish of the younger speakers was limited. One example of the shifting language situation comes from the mother-tongue claiming statistics; Hudson-Edwards and Bills (1982:147) found that more than two-thirds of speakers under twenty-five used English almost exclusively as the home language, while only 5 percent over twenty-five did so. Since their data were collected in 1975, this puts the year 1950 as a turning point in the language situation in New Mexico. Speakers born after that date had a much smaller likelihood of speaking exclusively Spanish in the home. The 1950s as a turning point is corroborated in Bowen’s (1952) description of the beginning of widespread English presence in San Antonito, a small New Mexican village located east of Albuquerque that was founded in 1835 by Spanish speakers from the nearby town of San Antonio. While Spanish at that time still had a strong presence in the community, Bowen (1952:12) predicted that Spanish would be replaced by English if the trends he saw in the younger speakers continued.

It has already been noted that the more isolated towns in New Mexico experienced the slowest shift to English (see Espinosa 1914-15). A case in point is

Arroyo Seco, a small New Mexican town ten miles from Taos but with limited accessibility by road until the early 1970s (Ortiz 1975:181). Ortiz (1975) studied the use and proficiency of both Spanish and English among young children and their siblings and parents in this community, a rural New Mexico town that experienced the late arrival of

English. Until the 1950s, Spanish was the primary language used in the community; participants over forty years old overwhelmingly reported Spanish as their mother tongue

(97% of 178 speakers) (Ortiz 1975:152). Among younger speakers, while the percentage

26 of those claiming Spanish as the sole mother-tongue was less than for the oldest adults, it was still in the majority for all age groups (89% for those 21-40, 71% for those 12-21,

67% for those 6-11, and 73% for those 2-5). While Ortiz reports an increase in the use of

English in this community, he does not claim that the community was undergoing shift to

English, although he notes that the town that was essentially monolingual in 1940 was now “characterized by a significant degree of bilingualism, especially among school-age youngsters and younger adults of the community” (Ortiz 1975:197). The domains of use for Spanish and English at the time were in somewhat of a diglossic situation, with

Spanish being used in the home and competing with English in the neighborhood and church. Overall, Ortiz (1975) found little evidence of incipient English-dominance and loss of Spanish in Arroyo Seco. Parents themselves did not worry that Spanish would be lost, even though they saw their children speaking much more English than they themselves did as children (Ortiz 1975:187). In other words, children in the early 1970s were speaking more English than their parents, but Spanish still held a strong presence in the community and individuals did not see the use of Spanish diminishing. Furthermore,

Ortiz (1975:187) found that parents saw English as the means for educational and economic success for their children. Bilingual education was introduced into Arroyo Seco around this time, a program which parents were generally in favor of. If the language situation in Arroyo Seco in the early 1970s tells us anything about bilingualism in New

Mexico, it is that English was introduced into rural New Mexico towns via schooling and contacts within larger towns that was sometimes necessary for work and job opportunities. These studies demonstrate the pervasive bilingualism in rural communities and villages beginning in the middle of the twentieth century, and the value placed on

English within these communities. This is important because favorable attitudes toward another language facilitate borrowing into the recipient language (Thomason 2001).

Additional studies provide details of the later generation in NM which grew up with both English and Spanish in the home. Gonzales Velásquez’ (1992, 1995) study of

Córdova, a small town fifteen miles from Española that was founded in the early 1700s, describes the language situation almost two decades later. Gonzales Velásquez (1992) conducted ethnographic observations for ten weeks in this community, focusing on intra- and inter-group female interactions. She found that the Spanish proficiency of the younger generations in Córdova was better than those of neighboring towns, including the biggest town in the area, Española (Gonzales Velásquez 1992:439). Her study asks why community members choose to speak one language over the other, and what factors influence language choice, including setting and interlocutor. Rather than viewing the use of English as a loss of Spanish, Gonzales Velásquez (1992:438) focuses instead on the

“cultural brokering” that the middle and younger speakers undertake to gain access to the market outside of Córdova. Furthermore, the addition of English into the speakers’ repertoires allows for innovation, including in the combination of both languages (code- switching) (Gonzales Velásquez 1992:438). Gonzales Velásquez (1995:61) emphasizes that women in this community are both innovators and conservators of their community language, Spanish. While at the time of writing her dissertation, the language was being maintained in Córdova (Gonzales Velásquez 1995:67), the almost exclusive use of

English in interactions solely between younger speakers indicated a shift to English, even in this town with a much deeper entrenchment of Spanish than neighboring towns. The shift was occurring in the author’s opinion due to “increased contact with English

28 institutions and more social distance from community traditions” (Gonzales Velásquez

1995:111). This study demonstrates the societal and economic pressures speakers faced to become fluent English speakers, in spite of their strong identification with their

Spanish heritage.

Taking into account proficiency and use in both English and Spanish in the entire state of New Mexico and southern Colorado, Bernal-Enriquez (2002) found that while

Spanish was a first language for most speakers in her sample, there was evidence of

English dominance in younger speakers and community-wide language shift. Analyzing

201 interviews from the NMCOSS corpus, Bernal-Enriquez (2002) found that regardless of region or gender, younger speakers used more English than Spanish and this, in turn, affected Spanish proficiency. Furthermore, speakers who experienced early bilingualism

(i.e. English acquisition between the ages of one and four alongside Spanish acquisition) reported lower levels of adult Spanish proficiency. The finding of language shift toward

English is further supported by the fact that age was found to be the only significant predictor of English proficiency and use. Furthermore, in spite of a full third of participants having high proficiency in both Spanish and English, Bernal-Enriquez

(2002:203-205) found a decrease in Spanish proficiency and an increase in English proficiency with age. Her findings indicate a shift towards English “paralleling loss of proficiency in Spanish” (Bernal-Enriquez 2002:210). It is worth pointing out that Bernal-

Enriquez judged proficiency subjectively, based on her subjective impression of their speech, and not by quantifying any particular linguistic feature. Furthermore, the fact that region or gender had no clear effects in Bernal-Enriquez’s (2002) study may point to a limitation in the NMCOSS, which attempted to sample the most proficient Spanish

29 speakers in NM, rather than collecting a random sample of speakers. In other words, analyses based on this corpus may overestimate the presence of Spanish in NM in the early 1990s.

As mentioned in the beginning of this chapter, NMS speakers have also been in contact with Mexican Spanish speakers. While most Mexican immigrants have settled in the southern half of the state, there is also a strong Mexican presence in the urban centers, specifically Albuquerque and Santa Fe, and the linguistic influence has reached all areas of the state. To illustrate, Bills and Vigil (2008:288) find that Mexican Spanish forms are displacing some Traditional NMS items, even in rural areas that were the slowest to be affected by external influences. For example, the word repollo ‘cabbage’, widely spoken in Mexico, is competing with the traditional NMS form col. Another factor to consider is that NMS is stigmatized in favor of Mexican Spanish, which is associated with the educated and standard variety (Bills & Vigil 1999:56, Kravitz 1985:143). This negative attitude toward the traditional dialect in light of an encroaching variety undoubtedly has consequences for the continued use of NMS features that contrast with Mexican Spanish.

In other words, a lack of apparent-time change in prosody could be due to the reinforcement of monolingual Spanish-like patterns via the influence of and exposure to

Mexican Spanish.

This section has described the bilingual situation in New Mexico throughout the twentieth century. The studies of language use and maintenance demonstrate that a shift to English in rural New Mexico was beginning in the 1950s, and was still in process in the 1990s. English has had a strong impact in New Mexico due in part to the extension of domains in which English has become used to the expense of Spanish and is manifested

30 most strongly in the decreased proficiency in the Spanish of younger speakers. The following section details the characteristic features of NMS, including the linguistic effects of contact with English in NMS, which sets the stage for an investigation of contact-induced influence on the prosody of NMS. Considering the bilingual situation in

New Mexico, we can ask how bilingualism has resulted in linguistic contact effects, and what predictions the specific unfolding of shift and bilingualism in New Mexico make for the likelihood of English to Spanish influence at the level of prosody. As I will demonstrate, the amount of English lexical borrowings and code-switching that characterizes New Mexican Spanish make it feasible that there would also be effects on the phonology of Spanish, including its intonational patterns, which is known to be highly susceptible to contact effects and which has been reported to be a characteristic feature distinguishing NMS from other varieties of Spanish. Furthermore, as will be shown in Chapter 3, the specific prosodic features considered in this study have all been shown to change in Spanish varieties in contact with other languages, including English in the United States.

2.3 Characteristics of New Mexican Spanish

NMS is characterized by innovative semantic, grammatical, and phonological features and lexical forms not found in other varieties of Spanish (Bills & Vigil 2008; Vigil &

Bills 2004). These features will be discussed here to give an overview of the status of

NMS as a unique dialect of Spanish. Some features unique to NMS are a result of contact with local languages, Mexican Spanish, and English. Most of the reported effects of such contact has been restricted to lexical items (e.g. Bills and Vigil 2008), although the extent

31 and length of contact with English makes structural influence likely. The result of contact with English will be discussed in the following section, which details specifically the research conducted on linguistic effects of the English-Spanish contact situation in New

Mexico. This section considers how what previous authors have said about the influence of English makes contact an explanatory variable in linguistic change in NMS.

The history of New Mexican Spanish is in many ways reflected in its lexicon.

Studies are quick to point out the “archaisms” abundant in this variety. The controversial term is used to describe lexical items that are still in use but are all but obsolete in the mainstream variety (Bills & Vigil 2008:32). For the most part, these lexical items are still found in other varieties of Spanish, although they tend to be found in rural and vernacular speech. Examples in NMS are cuasi ‘almost’ (standard casi), mesmo ‘same, self’

(standard mismo), and verbal forms such as trujieron ‘they brought’ (standard trajeron), and vido ‘he/she saw’ (standard vio) (Bills & Vigil 2008:32). Another example of a word still in use in NMS but not in other varieties (particularly Mexican Spanish) comes from regional words for ‘turkey’. Since this bird was encountered in the New World by

Spanish settlers for the first time, labels for the new animal were necessary. Choices ranged from gallina de la tierra ‘lit. New World chicken’ to guajolote, a borrowing from

Nahuatl. The lexical item gallina de la tierra, along with related gallo de la tierra ‘New

World rooster’ were the principle forms in the sixteenth and seventeenth century in New

World Spanish, and while these terms are still found in NMS, they have been replaced by other forms in Mexican Spanish, including the more common guajolote. Gallina/gallo de la tierra represents an archaism in NMS that tells of the variety’s history in the New

World. Borrowings from Nahuatl that came into the language prior to settlement in what

32 is now New Mexico are common, and many are still used in Mexican Spanish, which is one way these two varieties are tied together as a macro-dialect (Bills & Vigil 2008:15).

For example, tecolote ‘owl’ and zacate ‘grass’ are both borrowings from Nahuatl that appear in NM and Mexican Spanish, but not, for example, in Peninsular Spanish, where búho and pasto are used, respectively.

Previous authors have also noted distinctive features in NMS in terms of its grammar and syntax, although Bills and Vigil (2008:145) claim that there are no unique grammatical or phonological changes in NMS that do not occur in other nonstandard varieties of Spanish. For example, the second and third person root of the verb haber

(ha-) has extended to first person forms (e.g. hamos comido ‘we have eaten’ in place of hemos comido, and yo ha ido ‘I have gone’ instead of yo he ido). Verbal forms typically described as archaisms, such as vide ‘I saw’ and vido ‘he saw’ (mainstream vi and vio), also represent morphological traits of NMS, although these forms are characteristic of many rural varieties in the Spanish-speaking world in general (Bills 1997:168). Also characteristic of NMS is the use of –nos instead of –mos for first person plural in verbs that have antepenultimate stress. Examples include háblanos ‘we talk’ present subjunctive and habláranos ‘we talked’ past subjunctive, for hablamos and habláramos

(Bills & Vigil 1999:53).

In addition to the lexical, morphological, and syntactic features which categorize

NMS as a unique variety of Spanish, there are phonological and phonetic properties of

NMS that characterize this variety on a segmental level. Bills and Vigil (1999:54) outline various phonological features characteristic of NMS that differ from Mexican Spanish, the variety of Spanish that NMS is linguistically and geographically closest to. One of

33 these is ‘/s/ aspiration’, which refers to the realization of syllable-initial and syllable-final

/s/ as a glottal fricative, for example producing casi todos as cahi todoh ‘almost all’.

While syllable-final aspiration of /s/ is common in many varieties of Spanish, it is infrequent in interior Mexican Spanish. Furthermore, syllable-initial /s/ aspiration is less common worldwide, although it occurs in Spain, Colombia, El Salvador, Honduras and northern Mexican Spanish (Brown 2005:814, Lipski 2008:199; Lipski 2011). Another phonological feature characteristic of NMS and rare in other Spanish varieties is the paragogic -e (or -i) that follows stressed syllables ending in alveolar consonants.

Examples include trabajare ‘to work’ (standard trabajar), papele ‘paper’ (standard papel), and ratone ‘mouse’ (standard ratón) (Bills & Vigil 1999:54; Lipski 2008:206; see

Quesada Pacheco 2000:52-53 for an account of paragogic -e in an indigenous community in Costa Rica).

Given the uniqueness of NMS at the segmental level, it stands to reason that there are also unique intonational features. In the pioneering description of NMS that brought the attention of scholars to this variety, Hills (1906:706) observes that, “In certain cultivated valleys and in certain villages one may detect slight differences in vocabulary or in pronunciation - chiefly in accent and intonation.” However, he does not attempt to record or describe the difference. Aurelio Macedonio Espinosa, a well-known early scholar of Spanish linguistics, built on Hill’s work by writing comprehensive and lengthy descriptions of early twentieth century NMS (e.g. Espinosa 1914-1915). It is interesting that Espinosa does not mention intonation as a noteworthy feature of NMS, which means that it is possible he did not observe what Hills (1906) observed, or the present-day unique character of NMS prosody and intonation were innovations since Espinosa’s early

34 descriptions. Since Hills, there have been two scholars that have pointed out intonation as a characteristic dialectal feature of NMS. In Bowen’s (1952:33) detailed description of

Spanish spoken in San Antonito, he discusses the intonation of the traditional NMS dialect spoken in this small town as well as a Pachuco style also available to younger speakers in the community. Bowen’s description of the general intonation is hard to make sense of; however, he hints that there may be a special intonational pattern in utterance- final position (Bowen 1952:122). The Pachuco style he describes is characterized by a narrower pitch range and generally has a lower pitch than the “normal” intonation

(Bowen 1952:31-32). It is not clear, however, how widespread either intonation pattern is or whether it is contact-induced. This study hints at the possibility of an innovative intonational pattern developing during this time period, which is the same period in which the town began transitioning to English and the youngest people in the community were starting to become English-dominant while most of the monolingual Spanish speakers were over fifty years old (Bowen 1952:10-11).

The most detailed description of intonation in NMS comes from Lipski (2011), who attempts a cursory description of the “Norteño” intonation, in which he lumps together the dialects of northern Mexico and New Mexico. He attributes the unique intonation to the nuclear pitch accent (i.e. the phrase-final stressed syllable and any following atonic syllables), the final boundary tone, and the contour of the pre-nuclear pitch accents (i.e. non-phrase final stressed syllables) (Lipski 2011:89). In his description, he includes spectrograms from an Albuquerque speaker of traditional NMS. According to

Lipski (2011), the unique intonational pattern consists of a long rise in the tonic syllable of the final pitch accent. This long rise is characterized by a lengthened vowel with an

35 extended pitch rise throughout the tonic syllable that peaks within the syllable (Lipski

2011:89). In addition, the end of declarative utterances for this “Norteño” accent tend to end on a high pitch (as opposed to the typical low pitch for most varieties of Spanish), which “produces the impression of indecisiveness, irony, or ameloriation [sic], even when no such connotations obtain” (Lipski 2011:90). Pre-nuclear (non-final) pitch accents in the spectrograms Lipski provides occur with the pitch peaking within the stressed syllable, near the boundary of the syllable. As will be shown in the following chapter, where the pitch peaks in relation to the stressed syllable is variable across

Spanish dialects, and the norm for monolingual varieties is for the pitch to peak within the post-tonic syllable in this context. Dialects in which the pitch peaks within the stressed syllable have all been dialects of Spanish in contact with other languages.

Furthermore, English is a language in which the pitch peaks within the stressed syllable.

Lipski (2011:85) notes that in most varieties of Spanish, pitch accents in which the pitch peaks within the stressed syllable are associated with emphasis, and therefore early pitch peaks in pre-nuclear broad focus contexts creates the perception of being “overly emphatic” to listeners. Lipski’s description of “Norteño” Spanish provides a starting point for an analysis of intonation in New Mexican Spanish, and suggests that there are characteristic prosodic features in this variety to be explored in-depth, features which may be contact-induced.

2.4 Linguistic Effects of Contact with English

Throughout this chapter I have used the term ‘borrowing’ to describe features which have been transferred into NMS from English. The term ‘borrowing’ contrasts with Thomason

36 and Kaufman’s (1988:37) term ‘imperfect learning’, which refers to “the incorporation of foreign features into a group’s native language by speakers of that language”. Another way to describe this phenomenon is with the term ‘interference’, which describes the linguistic effects resulting from a group of speakers shifting to a target language. In interference, features of their L1 are produced in their L2. That is, the target language

(e.g. Spanish) exhibits linguistic elements from the shifting language (e.g. Quechua). The distinction between borrowing and interference is not trivial; different lexical and structural outcomes of contact are expected depending on the specifics of the contact situation. In borrowing, words tend to be borrowed first while structural borrowing, if it occurs, occurs later (Thomason & Kaufman 1988:40). Interference, on the other hand, tends to begin with phonology and syntax, and lexical borrowing is infrequent. Since

Spanish is the L1 of NMS speakers in this study, elements incorporated from English, their L2, would be considered ‘borrowings’. Borrowing scales predict that vocabulary is the first thing to be borrowed and as the intensity and length of the contact situation increase, other aspects of language structure may be borrowed (Thomason 2001:69-71).

After vocabulary, Thomason (2001:69) claims that what gets borrowed are easy-to- integrate structures, such as phonological features that are relatively superficial (e.g. stress placement) and syntactic features (e.g. word order). In younger NMS speakers who are becoming English-dominant, the distinction between the two types of transfer is not always as clear-cut. In the case of L1 on L2 interference, phonological transfer would be even more likely than in a borrowing situation, although whether the effects become a community-wide feature or not is more difficult to establish.

As predicted for a contact situation characterized by L1 speakers learning an L2 language, the most widely cited contact phenomena in the case of NMS (the L1) are word borrowings and code-switching (Bills & Vigil 1999:54, Bills & Vigil 2008:167, also see

Espinosa 1914-15). After New Mexico reached statehood, the speech community faced a new political reality, and required the terminology to converse about new technologies

(Bills & Vigil 2008:37). Words associated with political life and the industrial revolution were borrowed from English into NMS. Examples from this time period are mayor

‘mayor’, casa de corte ‘courthouse’, brecas ‘brakes, on an automobile’, and telefón

‘telephone’. Recall the discussion on ‘turkey’, which told of Spanish settlers facing this bird for the first time in the New World. One of the earliest terms used as a label was gallina de la tierra, a traditional NMS form; Bills and Vigil (2008:37) found in their survey conducted in the early 1990s that by this time, the Anglicism torque had become the second most popular form, competing with guajolote from Nahuatl and gallina de la tierra. There are many such examples in their Atlas of traditional NMS terms competing with or being replaced by English forms.

Lexical borrowings from English have been incorporated into NMS since the early 1900s, indicating how long English has been in contact with Spanish (although not the extent of bilingualism). Espinosa (1914-15) provides a comprehensive account of the

English influence on the Spanish of New Mexico up to that time. He notes that since

1846 English had been a strong presence in the state, and that English made its way into the Spanish vocabulary because of the English influence in schools, as well as the need for new terminology in areas of commerce, politics, and American machinery (Espinosa

1914-15:244-245). At the time the document was published, one third of the population

38 in New Mexico and Southern Colorado did not speak English (approximately 75,000 people), and they were located especially in the most isolated and rural areas of the state

(Espinosa 1914-15:245). Even so, English vocabulary and influence made its way into the Spanish of these regions. Espinosa (1914-15:245-246) lists words borrowed during the early years of occupation (e.g. jarirú 'how do you do'), terminology related to the railroad (e.g. pulman 'pullman'), and words introduced more recently via the school system (e.g. espeliar 'spell' and juipen 'whipping'). Espinosa (1914-15) details some 300 borrowings from English, and also lists semantic borrowings and loan translations.

Bowen (1952:46) also notes the influence that English has had on the vocabulary of NMS and attributes this to the prestige of English over Spanish in the region combined with the “traditional willingness of Spanish to accept borrowings.” More recent studies of

NMS also note the prevalence of English borrowings. Using the New Mexico Spanish-

English Bilingual corpus (NMSEB) (Torres Cacoullos & Travis 2015, Travis & Torres

Cacoullos 2013), a bilingual corpus with extensive code-switching, Aaron (2015) looks at single-item English origin nouns and determines whether they behave like borrowings or grammatically incorporated Spanish items. She (2015:477) finds that English-origin nouns perform certain discourse functions and that the norms are established by the community; rather than using English words as they function in English, “they serve specific, locally determined discourse functions that have been conventionalized within the community.” This study highlights the dynamic usage of two languages that are available to bilingual speakers, and also points to the depth of bilingualism in New

Mexico. This is a community that takes advantage of the two languages available to them by incorporating English lexical items into their Spanish and by code-switching during

39 interactions with other community members (see Gonzales Velásquez 1992, Gonzales

Velásquez 1995).

Wilson and Dumont (2015) note that an emergent grammar can be the result of speaking two languages regularly. Their study describes the bilingual compound verb hacer ‘to do’ + English Verb that has arisen in NMS and asks whether this compound verb is the result of easing the higher cognitive load and lexical gaps experienced by bilingual speakers. This bilingual construction combines the Spanish verb hacer, which provides the TAM, with a bare English infinitive that provides the lexical content. This same type of construction is found frequently in bilingual communities and is highly schematic, that is, the slot for English infinitives is open to a wide range of verbs. The construction arises as a way to accommodate bilinguals’ shifting between two languages.

Wilson and Dumont (2015:456) argue that this construction forms “a single unit integrated into Spanish grammar” based on prosodic and morphosyntactic behavior. In other words, this construction that emerges from bilingual usage becomes a part of the

Spanish grammar to accommodate the rapid switching between languages and with use becomes “entrenched and conventionalized” (Wilson and Dumont (2015:450). Indeed, code-switching has been posited as a mechanism for linguistic change (Thomason 2001,

Toribio 2004; see Torres Cacoullos & Travis 2011:241-242 for a review), and several studies of NMS describe the predominance of code-switching in this variety (e.g.

Gonzales Velasquez 1992, 1995). For example, Espinosa (1914-15:247) notes the predominance of code-switching (or “the problem of speech mixture”) in interactions throughout New Mexico and claims that it is responsible for the introduction of a great number of English words into NMS.

Several recent studies on NMS have analyzed code-switching contexts for potential influence from English into Spanish. These studies move beyond the realm of the lexicon, and provide the few studies focusing on the effect of English on the grammar and phonology of NMS. Torres Cacoullos and Travis (2011) test whether code-switching leads to grammatical convergence by analyzing rates and patterns of first-person subject expression in the Spanish of bilingual participants in the NMSEB. It is well-known that

Spanish has variable pronoun expression, whereas English has near invariable realization of person pronouns (see Shin & Montes-Alcalá 2014, Torres Cacoullos & Travis 2014,

Lindstrom 2017). Their study tests linguistic patterns of Spanish subject pronoun expression in contexts where code-switching is and is not present, and find that “first- person singular subject (yo ‘I’) expression in New Mexican Spanish follows the same patterning as has been identified for non-contact varieties, and this is the case regardless of the degree of bilingualism of the speakers” (Torres Cacoullos & Travis 2011:242). In other words, they do not find evidence of English influence on the grammar of Spanish with regards to first-person subject expression, and furthermore, code-switching does not appear to promote grammatical convergence.

Another study testing the influence of English on NMS grammatical patterns is

Benevento and Dietrich (2015). Using the same corpus of bilingual NMS speakers, their study compares the usage of post-verbal yo (1sg subject) in NMS both with the Spanish of non-contact varieties and within the context of code-switching in the speech of bilingual NMS-English speakers. Spanish allows for variable word order with regards to subject pronouns. For example, yo voy and voy yo are both perfectly acceptable word orders for ‘I go’ in Spanish. In contrast, ‘go I’ is not an acceptable variant of ‘I go’ in

English, as any native speaker will verify. Benevento and Dietrich (2015) test whether bilingualism with English has led to a decrease in the rate of post-verbal yo. They find that not only do NMS speakers produce a higher rate of post-posed yo (16%) than

Peninsular Spanish speakers (14%) (Benevento & Dietrich 2015:410), but that constraints on usage patterns are the same for highly proficient bilinguals as monolinguals, regardless of whether a code-switching context is present (Benevento & Dietrich

2015:416). It is not entirely surprising that evidence has not been found for English influence on the grammar of NMS, as grammatical features would not be expected to be as susceptible to borrowing as suprasegmental and phonological features of linguistic structure (Thomason 2001, Matras 2007, 2011).

Regarding phonological features, there is more evidence of English influence on

NMS, although the evidence is mixed. Balukas and Koops (2015) test whether code- switching is a mechanism for convergence in voice onset time (VOT), a feature which differs between Spanish and English. This study considers the VOT of both Spanish and

English tokens in the NMSEB with differing levels of proximity to code-switching boundaries. Although they initially predict that words following a code-switch point will show evidence of influence from the other language, they find that Spanish and English

VOT maintain the differences that are expected between them. Specifically, Spanish

VOT of word-initial voiceless stops displays no effect from English as expected. If anything, the VOT of English seems to exhibit influence from Spanish. The English

VOTs are shorter overall than the mean VOT of monolingual English varieties (Balukas

& Koops 2015:431). Furthermore, English VOTs decrease in the first few seconds after a code-switching point, which is in the predicted direction, but Spanish VOTs show no

42 such trend (Balukas & Koops 2015:432). They attribute the cross-language influence to the order of acquisition; since speakers in their study learned Spanish in the home and

English in school, regardless of adult proficiency, the language learned first is hypothesized as having a greater influence on the second language (Balukas & Koops

2015:436-437). Even though some speakers are more proficient in English and use

English more on a daily basis, the order of acquisition appears to be the most important factor in terms of convergence, according to their findings. Thomason (2001) also considers the direction of transfer to be affected by the specifics of L1 and L2, with the features most likely to transfer dependent on the type of situation speakers find themselves in. It may be the case that code-switching may not be the most likely mechanism for phonological and morphosyntactic transfer from L2 to L1, but rather the other way around (L1 to L2), which would explain why the studies of NMS testing

English convergence on Spanish via code-switching have found no evidence of English influence (Torres Cacoullos & Travis 2011, Benevento & Dietrich 2015, Balukas &

Koops 2015). Rather, one possible mechanism for phonological influence from L2 to L1 may be foreign pronunciations retained in borrowings (e.g. Sankoff 2004:647), as long as social factors are amenable to influence from the L2 (Thomason 2001).

Possible examples of phonological transfer via borrowings may be the allophonic variation of /r/ and /b/ in NMS. A phonological feature characteristic of NMS is the vocalization of /r/ before alveolar consonants which becomes pronounced as a retroflex approximant. The realization of /r/ in this context sounds similar to English [ɹ] and is salient to Spanish speakers. However, it is not necessarily the case that this sound has been influenced by English, as there are similar realizations of /r/ in other Spanish

43 speaking varieties not in contact with English (Bills & Vigil 1999:54). Vigil (2008:240) analyzes the allophonic variation of this retroflex approximant in the speech community of Taos and concludes that due to the high frequency of the English-like variant that

“[a]lthough it may not be concluded that contact with English prompted this structural change in the Spanish of all speakers of Taos, one may surmise that the nature of, and intensity of this contact situation may help to perpetuate it.” A similar conclusion is drawn by Torres Cacoullos and Ferreira (2000) in their study of the production of labiodental [v] as an articulation of /b/ in New Mexican Spanish, which is uncommon in other varieties of Spanish, in particular Mexican Spanish, but occurs more frequently in New

Mexican Spanish. Torres Cacoullos and Ferreira (2000) are interested in whether [v] occurs in New Mexican Spanish because of contact with English or as a result of internal language processes. Using a usage-based approach to study the variation, they predict that a high occurrence of [v] in low-frequency words and in the speech of younger speakers means that contact with English has influenced the realization of [v] in NMS.

They find that [v] occurs mostly in high-frequency, rather than low-frequency words, from which they infer that “although it is likely that contact with English has favored [v], its origin in New Mexico appears to be the Old Spanish labiodental” (Torres Cacoullos and Ferreira 2000:13). They note, however, that early studies of NMS such as Espinosa

(1930) and Hills (1938) do not mention the presence of the labio-dental [v], except in the speech of English-Spanish bilinguals. Vigil (2008) and Torres Cacoullos and Ferreira

(2000) demonstrate that the phonology of NMS has potentially been influenced by

English, although perhaps the influence is restricted to allophones that were already present in Spanish but whose rate of use was accelerated by contact with English.

Phonological change occurs through lexical borrowings, which we know has been frequent in NMS since the early 20th century. According to Sankoff (2004:643), the phonology of borrowed words lead to “subsequent adjustments in the phonology of the recipient language”. For example, if words with a foreign sound are borrowed, with time the foreign sound could become part of the receiving language’s phoneme inventory. It seems possible that suprasegmental features as well as segmental features could transfer via the borrowing of lexical items if, for example, stress patterns and reduction processes are borrowed along with the word itself.

Bowen (1952) claims that English influence on the Spanish of San Antonito is evident in the lexicon and phonology. He describes the Anglicisation taking over San

Antonito, in which English has become the language of the public-school system and the trade language of various businesses. At the time of publication, there were many

Spanish monolinguals in the town, all over 50 years old. The young children were all bilingual, some having a greater command of English than Spanish. Bowen (1952:13) notes that due to the influence of English, there are some words that have different meanings for the younger speakers than the older speakers. He also notes a phonological feature that occurs in the speech of bilinguals, but not monolinguals. Most of the bilingual informants inserted a glottal stop before vowels occurring word-initially, which

Bowen (1952:21-22) claims is a carryover from their English phonology. Considering the previous discussion, it is possible that this feature may have been incorporated into the

Spanish phonology via English borrowings first, which then spread to all words occurring word-initially. This particular feature has not been described elsewhere in the literature on NMS, so it is difficult to ascertain whether this is a contact-induced influence from

English. It may be that this feature was restricted to the Spanish of San Antonito and did not diffuse more widely; however, this example indicates that the bilingual situation between Spanish and English in traditional NMS communities was such that phonological influence from English into NMS was possible.

Considering the tide of English-speakers into New Mexico throughout the 20th century, and given the prestige associated with the English language, it is not surprising that English would have an influence on the varieties of traditional Spanish spoken in

New Mexico. Younger generations in the mid-1900s were already becoming English- dominant and less familiar with the Spanish of their parents and grandparents (Kravitz

1985:25, Bowen 1952:10-11). As discussed in section 2.2, the last half of the twentieth century saw widespread bilingualism with an increase of functional roles in English, leading to a perception of Spanish as being less economically advantageous and to the relegation of Spanish primarily to a language of the home (Bills & Vigil 1999:55). Such a situation would hypothetically open the doors for English influence on Spanish, beginning with lexical items and extending to phonological features. It is clear from the overview presented in this section that NMS has borrowed a large amount of vocabulary from English, including basic vocabulary such as the kinship terms dad and grandma

(Aaron 2015:467). According to Thomason (2001:70), when basic vocabulary words are borrowed, the contact is intense and is characterized by a greater number of bilinguals and favorable attitudes and social factors toward borrowing. It is at this stage that structural features are borrowed, including “prosodic features such as stress placement” and “loss or addition of syllable structure constraints”. In discussing a cline of borrowability, Sankoff (2004:658) also notes that phonology is highly borrowable, and

46 the mechanism by which phonology is borrowed is through foreign word borrowings which can have long-term influences on the recipient language’s phonology. Bowen

(1952) claims that the phonology of San Antonito Spanish speakers has been affected by increasing bilingualism with English. Further evidence that English may have had an effect on the intonation of NMS is that the most comprehensive early description of NMS

(Espinosa 1930) did not mention anything about prosody, but we know that a unique prosody in NMS has since developed (e.g. Bowen 1952, Lipski 2011).

The next chapter will give an overview of prosody and intonation in Spanish and describe other situations of Spanish bilingualism, including Spanish-English communities in the United States. The chapter demonstrates that the features considered in this study have been shown to change in Spanish via influence from the contact language, even in contact situations that are not as long or intense as the Spanish-English situation in New

Mexico. Research on suprasegmental features (e.g. rhythm and intonation) will help us understand whether prosody is more likely to exhibit convergence than segmental phonological features (as Matras 2007:39 postulates), and whether English-Spanish contact has contributed to the unique intonation of NMS (see Hills 1906, Lipski 2011,

Bowen 1952).

Chapter Three: Prosody

3.1 Introduction

This dissertation is interested in whether New Mexican Spanish prosody has been influenced by English, and aims to answer this question by analyzing three prosodic variables that differ between Spanish and English. The findings from these variables will inform a preliminary description of the pre-nuclear pitch accent of broad focus declaratives in New Mexican Spanish and increase our understanding of how different prosodic variables change in contact settings.

3.2 What is prosody?

Prosody refers to the suprasegmental characteristics of melody and timing (e.g. intonational and rhythmic properties of speech). It is well-known that rhythm and intonation play a key role in the perception of foreign or native accents, and listeners use prosodic cues to discriminate among varieties of dialects and different languages (Ramus

2002, BouladeMareüil & Vieru-Dimulescu 2006, Willems 1982). A multitude of definitions for intonation have been proposed (see Quilis 1993 for an overview), and the majority of definitions have in common that intonation refers to the movement of pitch across an utterance which tends to convey meaning, depending on the specific pitch patterns employed (Bybee 2015:67, Quilis 1993:410, Daneš 1960, Ladd 1996:6). In other words, pitch (the acoustic correlate of which is fundamental frequency, f0)1 is used in intonation languages (as opposed to tone languages) to distinguish among various

1 By and large, I’m following the use of ‘pitch’ to be mainly equivalent to ‘f0’, even though pitch is the perceptual correlate of f0. At points where the distinction is relevant, I will use the term ‘f0’.

48 sentence-level and pragmatic meanings. For example, the segmental string vas a la fiesta

‘you are going to the party’ in Spanish could be said with an intonation that conveys either a declarative or interrogative meaning, even though the word order may remain the same. This is the suprasegmental characteristic of intonation (i.e. features of sound that are above the level of consonants and vowels), and the relevance of intonation to sentence-level meaning is conveyed by either the declarative or interrogative meaning in this example.

Rhythm, along with intonation and stress, is another dimension of prosody.

Although rhythm and intonation both operate at the suprasegmental level, they have fundamental differences. Rhythm refers to “the patterning of prominent elements in spoken language, as perceived by the listener” (Nokes & Hay 2012:1). Rhythm is described as a gradient feature and does not convey pragmatic meaning. Rhythm is a temporal characteristic of language, and the perception of rhythmic timing is a by- product of lengthening and reduction processes, as well as the language’s phonotactics

(Miller 1984, Dauer 1987, Low & Grabe 1995, Grabe, Post & Watson 1999, Low et al.

2000, Dellwo, Fourcin, & Abberton 2007, Arvaniti 2009, Nava 2010). For example,

English speakers tend to reduce vowels in unstressed syllables, leading to a perception of consecutive syllables differing in length and prominence. English tends to be placed along the “stress-time” end of the rhythm categorization continuum (as opposed to

“syllable-timed”), precisely as a result of such processes.

Both rhythm and intonation have been of interest in Spanish prosodic research. A large area of intonation research is interested in identifying meaningful (i.e. phonological) contrasts in pitch movement across both prominent syllables and at the

49 boundaries of phrases. Furthermore, an important area of research in Spanish intonation is concerned with the similarities and differences in pitch contours and other prosodic features across Spanish dialects. Recently, there has been an increased interest in studying the development of Spanish intonation in areas where Spanish is in contact with other languages, or in terms of acquisition of intonational features, where Spanish is either an L1 or L2 (O’Rourke 2012). Contact effects on both rhythm (Robles-Puente

2014, Carter & Wolford 2016, Coggshall 2008, Thomas & Carter 2006) and intonation

(Colantoni & Gurlekian 2004, Colantoni 2011, O’Rourke 2005, Lleó, Rakow, & Kehoe

2004, Romera & Elordieta 2013, Simonet 2011, among others) have been found, leading to the development of distinct dialects due to external influences on the prosodic system.

This chapter is organized as follows. Section 3.3 will review the Autosegmental-

Metrical (AM) theory of Intonational Phonology (Pierrehumbert 1980, Ladd 1996), which many recent Spanish studies use as a model for analyzing intonation (e.g. Face

2002, Hualde 2002, Prieto et al. 1995, Prieto & Roseano 2010, inter alia). Using the same model facilitates a comparison of intonation across dialects, and the current study also adopts this model. Section 3.4 provides a description of Spanish prosody, highlighting the features that are considered in this study: rhythmic timing, peak alignment, and pitch variability, which have been shown to differ between Spanish and English in particular.

This section also discusses intensity, which is included as a variable in this study as it is an acoustic cue to prominence along with duration and pitch. Section 3.5 provides an account of prosody in contact. This section will describe how prosody, and the prosodic variables analyzed in this study in particular, have been shown to be susceptible to influence in contact settings, particularly in situations where Spanish is in contact with

50 other languages. The ultimate goal of this chapter is to demonstrate how Spanish and

English contrast in the prosodic parameters of this study in order to set the stage for the analysis of hypothesized Spanish-English contact effects in New Mexican Spanish prosody.

3.3 The Autosegmental-Metrical (AM) Model of Intonational Phonology

This dissertation uses the Autosegmental Metrical (AM) theory of Intonational

Phonology as a framework for describing intonation in NMS (Gussenhoven 2004, Ladd

1996, Pierrehumbert 1980). This theoretical model of intonational phonology developed from Pierrehumbert’s (1980) landmark dissertation on English intonation, and has since been applied to various Spanish intonation studies, using the Tones and Break Indices

(ToBI) system of transcription adapted for Spanish (SpToBI) (Beckman, Díaz-Campos,

Tevis McGory, & Morgan 2002:10, Face & Prieto 2007, Estebas-Vilaplana & Prieto

2008). The AM model presupposes a phonological representation, which consists of underlying tonal targets and their combinations. There are two types of tonal targets within this framework: pitch accents, consisting of H (high) and L (low) tones on metrically prominent syllables, and boundary tones (again made up of H and L tones), which occur at the end of both intermediate (iP) and intonational phrases (IP). The pitch contour is gradient and represents the phonetic movements connecting the targets. Pitch accents may consist of one tone (e.g. H* or L*, starred because of the primary association with the stressed syllable) or may be bitonal, consisting of a rise or fall before or after the starred tone (e.g. L + H* refers to a rise culminating in a High tone; H* + L refers to a

High tone associated with the stressed syllable, followed by a fall). The schema in Figure

1 displays the idealized pitch accent L+>H*, which is the general pre-nuclear pitch accent in Spanish broad focus declaratives (Prieto & Roseano 2010). The > symbol means the peak is delayed; therefore, L+>H* represents a pitch accent characterized by a rise throughout the stressed syllable with the f0 peak aligned within the post-tonic syllable (Estebas-Vilaplana & Prieto 2010:19).

Figure 1. Schema of L+>H* pitch accent. The shaded area represents the accented syllable.

A distinction important to the AM framework is that between events and transitions, events being the tonal targets (L or H), and transitions (rises and falls) being the movements between events. In this framework, events are primary, and movements represent phonetic continua that are transitions between underlying tonal targets (Ladd

2008:175). In other words, events are fundamental because different tonal targets in a pitch accent represent phonological distinctions between meaningful categories, such as between statements and questions, and between different types of focus structure (Hualde

2000). Although pitch is gradient, alignment - the temporal coordination of tonal targets with consonants and vowels (Ladd 2008:169) - of associated tones to the segmental structure is phonologically specified (Pierrehumbert 1980). The pitch accent displayed in

Figure 1 (L+>H*) represents a phonological category, although phonetic variation in the actual production is normal (as, for example, /p/ is a phoneme in English that is produced

52 with aspiration in onset position, though the specifics of the aspiration differ from realization to realization). In other words, the AM model presupposes that intonation can be analyzed phonologically, much like segmental features (Ladd 2008:3).

The utility of such an approach is that pitch accents function contrastively because they are phonological (Willis 2003:3). Descriptions of intonation in a particular language using the AM framework strive to determine a phonological inventory of pitch accents that are meaningfully contrastive in that language. Furthermore, the phonological analysis can be informed by a careful phonetic investigation. The availability of easily accessible acoustic software has made such studies possible (Hualde 2002).

Several studies show that f0 aligns consistently with the segmental string for pitch accents in several languages, such as Spanish, German, and Greek (Arvaniti, Ladd &

Mennen 1998, Ladd, Mennen & Schepmann 2000, Prieto et al. 1995), even regardless of speech rate (Ladd, Faulkner, Faulkner & Schepmann 1999). Atterer and Ladd (2004) look at pitch differences in Northern and Southern German by examining the points at which pitch targets are aligned with segments. Atterer and Ladd (2004) recorded six points (or segments) for each utterance: the beginning of the consonant preceding the accented vowel, the onset of the accented vowel, the onset of the following consonant, the onset of the following vowel, the point of minimum local F0 (L), and the point of maximum local f0 (H). They found that the speakers of both varieties of German align H within the following unstressed vowel, and align L “well within the initial consonant of the stressed syllable or even early in the stressed vowel” (Atterer & Ladd 2004:185). This differs from Dutch and British English, languages in which the f0 peak is aligned within the stressed syllable. In addition, the beginning of the accentual rise is later for the

Southern German speakers than the Northern German speakers. Kügler (2004) also looks at the alignment of associated tones to the segmental structure by comparing pitch between two varieties of German, Swabian and Upper Saxon, and focuses on the nuclear rising pitch accent. He measures f0 at four different points within the periodic signal of the stressed syllable (including f0 minimum and maximum) and finds that in Swabian

German the pitch peak is realized within the accented syllable, differing from reports on other Southern German dialects, where the pitch is said to peak on the post-tonic syllable

(Kügler 2004:90). These studies show that measuring f0 in relation to the segmental structure is an effective way to compare pitch across language varieties and is informative for distinguishing between pitch accent types such as L+H* and L+>H*, which are meant to be phonologically distinct within a language under the AM model of intonational phonology. Within each pitch accent type, however, the placement of the f0 minimum and maximum exhibits phonetic gradation. At some point, however, the gradation is perceived as a separate category of pitch accent (see Section 3.6 on Peak

Alignment).

The AM literature also distinguishes between pre-nuclear and nuclear pitch accents, which in most varieties of Spanish have a different phonological shape. The nuclear accent refers to the final pitch accent in a phrase (Ladd 2008:133, Hualde

2004:221), and pre-nuclear accents refer to non-phrase final prominent accents on

(typically) lexically stressed syllables. According to Hualde (2002:5), almost every lexically stressed syllable of content words in Spanish declaratives carry a pitch accent.

For example, the Spanish phrase Mariana comió una manzana may have pitch accents on the lexically stressed syllables of Mariana and comió, and a nuclear accent on -za- of

54 manzana, followed by a boundary tone on the post-tonic syllable na, transcribed with a dash for intermediate phrases (e.g. H-) and a percentage sign for intonational phrases

(e.g. L%) in ToBI. The difference between intermediate and intonational phrases depends on the boundary strength, with the perceived juncture being greater for the intonational phrase (Beckman, Hirschberg, & Shattuck-Hufnagel 2005:15). The boundary tones convey the final pitch level of the phrase, and are used by speakers to mark the end of the phrase (see Ladd 2008 for a more detailed description).

As mentioned, intonation interacts with pragmatic and discourse-level meanings.

One of the distinctions used in this study is that between broad and narrow focus. An utterance has broad focus if the size of the constituent in focus is larger than the object noun-phrase, such as, for example, if the entire sentence or verb phrase is in focus

(Bishop 2012:241). Ladd (2008:214) provides the following as an example of narrow focus with five contrasting with three, since the issue is the number of francs:

1. I didn’t give him three francs, I gave him five francs.

On the other hand, if the focus is on a larger constituent, such as, I didn’t ignore him, I gave him five francs (where the verb-phrase gave him five francs contrasts with ignore him), then the focused constituent is larger than a single noun-phrase. In other words, no one word of the utterance is highlighted or contrasted. Narrow focus contrasts a word with some other word or object phrase from “a more or less unlimited set of possibilities”

(Ladd 2008:215). For example, if John painted the shed yesterday is said in response to the question Who painted the shed yesterday?, then John is the focus constituent and the

55 utterance has narrow focus. In this example, the possible set of words that could replace

John includes people capable of painting the shed. Contrastive focus is another type of focus often mentioned in intonation studies (e.g. Face 2002, García 2011). Contrastive focus “signals some sort of contrast or emphasis on the stressed word” (Ladd 2008:216).

For example, if asked, “Are we going on the flight to Madrid?”, and the response contrasts Barcelona with Madrid, as in, “No, we’re going to Barcelona”, then the contrastive focus is on the word Barcelona. Face (2002:4) considers contrastive focus to be a subset of narrow focus.

In sum, broad focus refers to utterances in which no one word is highlighted or emphasized more than others, and narrow focus refers to cases where a word of the utterance is highlighted or contrasted with another possible word. As will be shown in the following section, pitch accents may be different depending on the type of focus, as is the case for Spanish, in which broad focus items have a different tonal contour in pre-nuclear accents than items in narrow focus (Beckman et al. 2002). In the current study, only broad focus contexts are examined.

The following section describes the major findings in Spanish intonation, paying particular attention to the descriptions for Mexican Spanish, which is the variety geographically and historically most closely related to New Mexican Spanish.

3.4 Spanish Prosody

Work on intonation in Spanish was pioneered by Navarro Tomás, whose 1944 monograph is noted for its systematic observations that have proven accurate in light of acoustic analyses. For example, Navarro Tomás observed the tendency for Spanish to

56 align the f0 peak within the post-tonic syllable in pre-nuclear broad focus declaratives

(transcribed as L+>H* in current SpToBI conventions, see Figure 1). He was also the first to describe dialectal differences in Spanish intonation. In the past two decades, empirical research in Spanish intonation has surged, while many questions remain unresolved (see Hualde 2000 and Beckman et al. 2002 for a discussion of current issues in Spanish intonation research).

Much recent work has involved determining labels for declarative and interrogative pitch accents. Though intonation is highly variable, there are generalizations about intonation in most varieties of Peninsular and Latin American Spanish that are generally agreed upon: (1) in broad focus, pre-nuclear accents in declarative utterances, the f0 rises throughout stressed syllables and reaches its highest point in the post-tonic syllable, and (2) declarative utterances are characterized by downstepping, the process in which the f0 peak successively lowers from peak to peak within an utterance (Face

2003:117-118, Prieto et al. 1995). Therefore, if the utterance is downstepped, the final H tones of the utterance will have a lower f0 than the first H tones. Prieto and Roseano

(2010:10) compare intonational features across multiple dialects of Spanish, and conclude that in a majority of Spanish varieties (with the exception of Dominican

Spanish), the nuclear (i.e. final) accent has a low (L*) tone and the final boundary tone is

L%. Schematics for L* and L% are displayed in Figure 2.

L*:

L%:

Figure 2. The schematic for L* displays a low level that is at the bottom of the speaker’s f0 range for the phrase. The schematics for the L% boundary tones are realized as a low plateau or falling tone at the minimum of the speaker’s f0 range (adapted from Estebas-Vilaplana & Prieto 2010:19-20).

Mexican Spanish spoken in the Distrito Federal shares several pitch accents in common with Peninsular Spanish. In a description of this variety using the SpToBI labeling conventions, de-la-Mota and colleagues (2010:320-321) claim that L* for broad focus declarative nuclear pitch accents and L% for the boundary tone of broad focus statements are also found in their corpus. They list two pitch accents that are found in pre-nuclear broad focus declaratives: H* and L+>H*. H* represents a high plateau throughout the stressed syllable with no preceding f0 valley that is relatively high compared to the surrounding phonetic context. In addition, they provide a pitch accent for broad focus nuclear accents in declaratives not mentioned for Peninsular Spanish, L+H*, which is a rise in f0 throughout the stressed syllable culminating in a peak located at the

58 end of the accented syllable. The pitch accent L+H* is also found in narrow focus accents in both Mexican and Peninsular Spanish, and various interrogative contours (Estebas-

Vilaplana & Prieto 2010:19). While the pitch accent L+>H* is the phonological category for the pre-nuclear broad focus declaratives in monolingual varieties of Spanish, there are varieties of Spanish that do not have this pitch accent, but rather have the L+H* pitch accent for this category. For example, Elordieta (2003:92) claims that L+H* is the standard one for pre-nuclear broad focus declaratives in Basque Spanish. Varieties that have L+H* for pre-nuclear broad focus contexts appears to be restricted to situations where Spanish is in contact with other languages, such as Spanish with Basque (Elordieta

2003).

Table 1 lists the various pitch accents described thus far, and includes the contexts they are found in that are relevant to this study (for an overview of all contexts, such as yes-no questions and vocatives, and for other pitch accents used in Spanish, see

Prieto & Roseano 2010, and see Sosa 1999 for a cross-dialectal description of intonation in Spanish).

Table 1. Overview of pitch accents and boundary tones found in pre-nuclear and nuclear broad and narrow focus declarative contexts in Peninsular and Mexican Spanish. Adapted from Estebas-Vilaplana and Prieto (2010:19-21) and de-la-Mota et al. (2010:320-322). Pitch Schema Description Accents, Boundary Tones

L* Characterized by a low plateau that is at the bottom of the speaker’s f0 range for the phrase. Found in nuclear position of broad focus

declaratives in Mexican and Peninsular Spanish.

L+H* Characterized by a rise in f0 throughout the stressed syllable culminating in a peak located at the end of the accented syllable. Found in nuclear accents of broad and narrow focus declaratives in Mexican Spanish, and in narrow focus in both Peninsular and Mexican Spanish.

L+>H* Characterized by a rise throughout the stressed syllable with the f0 peak aligned within the post-tonic syllable. Found in pre-nuclear position of broad focus declaratives in Peninsular and Mexican Spanish.

L% Characterized by a falling pitch (left) or a low plateau (right) at the minimum of the speaker’s f0 range. Found at the end of broad and narrow focus declaratives in Peninsular and Mexican Spanish.

Studies comparing intonation in different varieties of Spanish have gone about quantifying f0 movements that inform a phonological analysis of pitch accents (e.g.

O’Rourke 2005, Willis 2003). This dissertation study is interested in determining what phonetic variation exists within the L+>H* pitch accent category in NMS. If, for example, there is a center of variation of pitch peak alignment before the boundary of the stressed syllable, this would indicate that L+H* is a possible pitch accent for this context.

Otherwise, if the center of variation is after the boundary of the stressed syllable, as is the pattern for monolingual varieties of Spanish, then it can be determined that L+>H* is likely the general pitch accent in this context for this variety as well. As we will see, the variation in this pitch accent is of interest when considering varieties of Spanish in contact with other languages.

Establishing dialectal differences is also informed by comparing the acoustic dimensions of prosody, which include pitch peak alignment, pitch range, and prosodic timing (cf. Willis 2003:7-13). For example, alignment is the starting point for recognizing and categorizing pitch accents that correspond to functional differences, such as statement type (declarative vs. Interrogative), focus (broad vs. narrow), and category

(pre-nuclear vs. nuclear). Differences in pitch range across dialects have also been documented, sometimes meaningfully distinguishing between different categories. In

European Portuguese, for example, increased pitch range has been shown to correspond to narrow focus (Frota 1998). In Willis’ (2003) study on Dominican Spanish, he quantifies alignment, range, and duration to form a basis for characterizing Dominican

Spanish intonation.

Patterns of alignment, range, and prosodic timing are reported to differ between

Spanish and English, and therefore allow for a point of comparison between the two languages in terms of influence from English into Spanish. The following section reports on the susceptibility of prosody to contact-induced change in general, which is followed by a discussion of each variable included in this study and what previous studies have found regarding their characteristics in monolingual and contact varieties of Spanish.

3.5 Prosody, contact, and change

There is a paucity of studies analyzing the effects of contact on intonation and prosody, but the studies that exist show a remarkable vulnerability of prosody to change. When intonation is mentioned by linguists specializing in language contact, it seems to be taken for granted that intonation is particularly susceptible to cross-linguistic influence. For example, Mackey (2000:48) says that, "[o]f all phonological features, intonation is often the most persistent in interference and the most subtle in influence." Matras (2007:38-39) notes that "prosody is a domain of phonology that is particularly prone to contact", and that a complete convergence of prosodic systems is more likely than segmental phonological features in a situation of contact. He admits, however, that the empirical

62 data on prosody he bases his claim on is small. He attributes prosody’s vulnerability to contact-induced change to the operation of prosody at the speech act and utterance level, which makes disconnecting it from the word level easier for speakers. Matras (2011:222-

223) adds that structures operating at the discourse level, as prosody does, are more susceptible to borrowing than devices operating at the clausal or word level. Matras

(2011:223) cites Romani as an example of a language whose dialects have undergone prosodic convergence with contact languages, but admits that prosody in contact remains under-investigated.

Empirical investigations of prosody in languages in contact has increased, providing evidence that prosody is indeed likely to change in contact settings. Bullock

(2009) analyzes prosodic features in the French of Frenchville, Pennsylvania, a linguistic isolate community in a long-term contact situation with English. Bullock (2009) points out a salient prosodic feature characteristic of this variety which seems to be a product of contact with English. In standard French, emphatic or contrastive focus is expressed via word order and phrasing. English, on the other hand, marks emphasis and contrastive focus via prosodic prominence, while lexical items remain in situ (e.g. the book of MY friend, as opposed to someone else's, with emphasis on 'my'). Frenchville French has the option to mark prominence via prosody in this manner, which Bullock (2009) attributes to convergence with English. Bullock's (2009:189) study provides evidence that "the prosodic system in a long-term contact setting is highly vulnerable to change." The situation of French in the United States is similar to Spanish in New Mexico in that it provides an example of a societally dominant language’s influence on the L1. Another example of borrowing of prosodic features comes from Majorca, where Catalan is the

63 native language of the island. Remarkably, the native Spanish of recent arrivals shows evidence of Catalan prosodic patterns. In particular, the nuclear accent in both declaratives and interrogatives differ in the contour between Catalan and Spanish. Due to accommodation to native Catalan speakers producing L2 Spanish, newcomers to the island adopt contours in their native Spanish that resemble L2 Spanish of Catalan speakers. Romera and Elordieta (2013) demonstrate that intonational patterns can be borrowed from the L2 into the L1 of adult speakers.

Prosodic features that have been commonly reported to change in contact settings are pitch accents and final boundary tones. For example, Alvord (2010) examines the falling pattern that is associated with Cuban Spanish absolute interrogatives, and finds that young Miami Spanish-English bilinguals produce both that structure and a rising pattern prevalent in English when speaking Spanish. This leads Alvord (2010) to conclude that the prosodic system of Miami Spanish has undergone contact-induced innovation due to English. Fagyal (2005) finds that the French pitch accent inventory of young Arabic-French bilinguals in an immigrant suburb of Paris has been influenced by the substratum language, Arabic. In particular, whereas French has a simple rise on the final syllable, the young male speakers born in France of North-African descent (i.e.

Beurs) have this option plus a pitch accent characterized by a rise on the penultimate syllable, accompanied by optional lengthening and followed by a fall. Furthermore, whereas this may have come into this French variety via substratum influence, it is found in young speakers of the community whose parents are not Arabic speakers (Fagyal

2005:102). Therefore, the prosodic pattern seems to be becoming a feature of the Beur

French vernacular, regardless of language background of the speaker.

Queen (2001) finds that bilingual children acquiring two languages (in this case

Turkish and German) have multiple intonational options available to them, including a

"fused" system that is innovative and influenced by both languages, but is not identical to either. Also looking at utterance-final pitch accents, Simonet (2011) examines how the

Spanish spoken in Majorca is influenced by Catalan, the native language of the island. He finds that older speakers pattern like Peninsular monolingual Spanish speakers, but younger speakers, in particular younger females, are converging their Spanish towards a

Catalan-like pattern. The native Catalan speakers use concave-falling contours (L*) in their utterance-final pitch accents both in Catalan and Spanish, whereas the L1 Spanish pattern is a rising-falling or convex-falling contour. Younger females are leading the change in their Spanish toward a Catalan-like concave-falling contour from exposure to

Catalan L2 Spanish (Simonet 2011:180). Overall, transfer of intonational patterns occurs both when Catalan-dominant bilinguals speak Spanish and produce Catalan patterns, and when Spanish-dominant bilinguals use Catalan patterns in their L1, Spanish. This leads

Simonet (2011:194) to conclude that “intonational contours may be transferred to other languages in contact situations both through substratum and adstratum (borrowing) processes.” These examples demonstrate that there are multiple pathways toward prosodic change, including transfer during simultaneous acquisition (Queen 2001) and borrowing of L2 patterns (Romera & Elordieta 2013, Simonet 2011).

In sum, there is ample evidence that prosody is susceptible to contact-induced change. In order to explore whether English has influenced the prosody of Spanish in

New Mexico, it is crucial to find prosodic features which differ between Spanish and

English. Features which fit this description are pitch peak alignment, rhythm, and pitch

65 range. An analysis of these features across three generations of New Mexican Spanish speakers with differing levels of exposure to English can shed light on how language contact affects intonation and how different prosodic features change either in conjunction with each other or at different rates, which would suggest that a hierarchy of prosodic features in terms of their susceptibility to contact-induced change is appropriate.

Such a hierarchy would be a novel contribution to the study of prosody in contact.

The following sections will describe the prosodic variables of interest in this study, how they have been described for Spanish and how they differ in English, and includes studies of Spanish and English in contact that have examined these particular variables. This will set the stage for the current study, which is interested in whether these variables play a role in the unique intonation of New Mexican Spanish, whether throughout the 20th century these variables have exhibited change, and whether social dimensions play a role in this change.

3.6 Peak Alignment

Pitch peak alignment is the placement of the f0 in relation to the prominent, or tonic, syllable, and can be affected by factors such as syllable structure, speech rate, and position within the utterance (e.g. Prieto et al. 1995, Barnes & Michnowicz 2013). Since we are interested in the alignment of the H tone in the Spanish pitch accent L+>H*, we are interested in the position of the maximum f0 in relation to the boundary of the tonic syllable. Alignment has been studied extensively in many languages (e.g. Arvaniti et al.

1998 for Greek, Silverman & Pierrehumbert 1990, Steele 1986 for English, Kügler 2004 for German, among others). Indeed, alignment is likely the most researched acoustic

66 correlate of intonation in Spanish. Studies analyzing alignment in order to establish contrastive pitch accents are numerous in monolingual (Face 2001, Prieto et al. 1995,

Sosa 1991, 1999, Hualde 2000, Willis 2000, Garrido, Llisterri, de-la-Mota, & Rios 1995,

Llisterri, Mann, de-la-Mota, & Ríos 1995, Prieto et al. 1995, Prieto 1998) and bilingual

(O’Rourke 2004, O’Rourke 2005; Elordieta 2003, Colantoni 2011, Hualde & Schwegler

2008, Michnowicz & Barnes 2013, Garcia 2011:26) varieties of Spanish.

Productions of pitch accents naturally occur with phonetic gradation, although at a certain point alignment differences lead to categorical differences in pitch accents which are perceived categorically (e.g. L+H* vs L+>H*). For example, Pierrehumbert and

Steele (1989) demonstrate how the pitch accents L*+H (L tone associated with the stressed syllable followed by a rise) and L+H* (rise leading to an H tone associated with the stressed syllable) have contrastive functions in English. In their experiment, they provided participants with stimuli that varied the alignment of f0 in 20 ms increments.

When subjects were asked to produce the rise-fall pattern they heard, they categorized the productions into two categories corresponding to the two pitch accents, even though they heard stimuli falling in between the two types. This study demonstrated that there are at least two phonologically contrastive pitch accents in English, and they are created by the alignment of L and H tones anchored to the tonic syllable. Differences in peak alignment are important to quantify, as this gradient dimension forms the acoustic basis for categorical pitch accent distinctions. The importance of peak alignment is apparent when considering that listeners may phonologically misinterpret stress if the phonetic alignment of tones deviates from the expected pattern (Ladd 1996:129). As O’Rourke

(2005:74) notes, speakers of Italian, a language characterized by peak aligned early in the

67 stressed syllable, may encounter difficulty when communicating with speakers of languages who place the peak late in the syllable, such as in English and German. Indeed, since the pitch accent L+H* is used in Spanish in contexts of narrow focus and emphasis, speakers of dialects of Spanish that align the H tone within the tonic syllable in broad focus contexts may be “perceived as overly emphatic” to speakers of dialects with

L+>H* (Lipski 2011:85).

The default pitch accent for pre-nuclear broad focus contexts (L+>H*) in Spanish is of particular interest to this study precisely because of its dialectal variation, which tends to occur in situations of language contact (see Michnowicz & Barnes 2013,

Colantoni 2011, O’Rourke 2005, Elordieta 2003; also discussed below in Section 3.6.1).

The L+>H* pitch accent is characterized by a rise throughout the stressed syllable that does not peak until the post-tonic syllable (Estebas-Vilaplana & Prieto 2008). The H tone is associated with (or anchored to) the stressed syllable, but is phonetically aligned within the post-tonic syllable. Figure 3 below shows an example of late peak alignment in the word funciona ‘functions’ from the spontaneous speech of a male Spanish speaker from

Paraguay.

Figure 3. Late peak alignment in pre-nuclear position on the word funciona, within the utterance entiendo perfectamente como funciona todo ‘I understand perfectly how everything works’ (Bittar & Van Buren 2017)

Studies that attempt to describe the inventory of Spanish pitch accents generally elicit read or semi-spontaneous speech by native speakers using prepared contexts (see for example Face & Prieto 2007, Estebas-Vilaplana & Prieto 2008 for revisions to the original SpToBI transcription). Face (2003) considers how Spanish intonation generalizations formed through laboratory speech studies fare in spontaneous Spanish speech. He finds that in pre-nuclear declaratives, a post-tonic peak alignment occurs not

100% but only 75% of the time, and that the early alignment in 25% of the cases is not necessarily due to narrow focus. However, Face (2003:125) speculates that speakers make use of early alignment for a specific purpose, other than those that are already known (i.e. narrow focus and in imperatives). Therefore, it is clear that the pitch accent

L+>H* shows variation in the phonetic degree of alignment/displacement, even in monolingual Spanish varieties. However, the center of the variation in spontaneous speech of monolingual varieties is in the expected, delayed shape; in other words, the majority of tokens still exhibit the late alignment pattern. This pitch accent is

69 characterized by the f0 peaking in the post-tonic syllable, a characteristic which is the norm in Spanish pre-nuclear broad focus contexts. This dissertation study is interested in the alignment of the f0 to the boundary of the stressed syllable in NMS to determine what phonetic variation exists within the L+>H* pitch accent category in NMS.

3.6.1 Peak Alignment Variation in Contact Varieties of Spanish

There are several dialects of Spanish that are reported to exhibit differences in alignment for the default pre-nuclear broad focus declarative pitch accent, typically in situations where speakers of an indigenous language are in contact with Spanish speakers. This section will report on the literature, showing that this feature is ripe for investigation in situations of Spanish in contact with other languages, specifically languages that exhibit early alignment in this same context, such as English.

Typically, variation in pitch peak alignment is found in Spanish varieties that are in contact with indigenous languages, with early alignment being a result of interference from the speakers of the indigenous languages as they acquire Spanish (i.e. substratum influence). For example, Michnowicz and Barnes (2013) find a high percentage of early peak alignment in the speech of eight speakers of Yucatan Spanish, a variety in contact with Yucatec Maya. They quantify peak alignment by measuring the duration of the stressed syllable and the distance from the f0 peak to the end of the stressed syllable. In their data, 64% of peaks in pre-nuclear declarative contexts align within the tonic syllable

(Michnowicz & Barnes 2013:227). Studies of this feature in other contact varieties of

Spanish report similar findings. O’Rourke (2005) uses this same methodology to analyze peak alignment in two varieties of Peruvian Spanish, one marked by widespread

70 bilingualism with Quechua (Cusco Spanish) and one with lower levels of bilingualism with Quechua (Lima Spanish). She finds regular early peak alignment in Cusco Spanish but not in Lima Spanish. She also analyzes alignment patterns in Quechua, and finds that this substratum language also exhibits early peak alignment, which leads her to posit influence from Quechua on Cusco alignment patterns. Bilingual Spanish-Basque speakers have also been found to exhibit early alignment in pre-nuclear broad focus declaratives, presumably due to influence from the northern Basque dialect spoken in Lekeitio

(Elordieta 2003:86). However, the speakers also exhibit patterns in their Spanish different from Basque, such as pitch rises in stressed syllables that differ from the Basque H*+L pitch accent (Elordieta 2003:92). In other words, their intonation differs from both

Basque and Spanish, even though Basque is considered to be their native language. Such

“mixed systems” are not unheard of; recall that Queen (1996, 2001) finds final contours in the speech of bilingual German-Turkish children that draw from both languages available to them but also include innovative patterns. This finding leads Queen

(1996:242) to conclude that in language use, “bilingual speakers have a larger set of linguistic options through which to communicate and with which to develop new and unique patterns”.

First language acquisition studies have considered how alignment is acquired by bilingual children who speak languages with different patterns. Lleó and colleagues

(2004:5) consider a pre-nuclear pattern that differs between German and Spanish. The pitch accent is falling (H*L) in German and rising (L*H) in Spanish.2 They find that one

2 At the time Lleó et al. (2004) wrote the article, the SpToBI convention for the pre-nuclear broad focus pitch accent characterized by a rise throughout the stressed syllable reaching its peak in the post-tonic syllable was L*+H (Beckman et al. 2002). There has been considerable debate regarding the best way to transcribe this pitch accent (Hualde 2002:103, Face & Prieto 2007, Estebas-Vilaplana 2007), but the current

71 child produces both patterns in a monolingual-like way, but one bilingual child substitutes one for the other. More often than not, the child uses the German pattern, which they argue is due to exposure to a higher frequency overall of the H*L pattern and to markedness of the post-tonic pattern. Considering that in monolingual Spanish, the pitch accent transcribed as L+H* (a rise throughout the tonic syllable that peaks within the boundary of the syllable) is found in narrow focus and nuclear position, it seems plausible that L+>H* would be substituted by L+H* due to higher frequency in the input of L+H*, particularly when the other language of a bilingual speaker only has the L+H* pattern in broad focus contexts. Lleó et al.'s (2004) findings explain why the change to early alignment in pre-nuclear broad focus declaratives in Spanish may be so widespread across contact situations.

Where native speakers of a language characterized by early alignment (the L1) learn Spanish (the L2), the alignment patterns of Spanish are susceptible to interference

(e.g. O’Rourke 2005). It has also been shown that the prosody of a subset of a community can affect the speech of the larger community, with regards to alignment, as exhibited by

Spanish in Buenos Aires. Colantoni (2011:295) finds early peak alignment in 80-100% of tonic syllables in Buenos Aires Spanish, a variety that experienced contact with Italian due to a massive influx of Italian immigrants between the mid-19th and early 20th centuries (Fontanella de Weinberg 1987). Colantoni and Gurlekian (2004:116) argue that early alignment became a widespread feature in the Spanish of the entire speech community due to both indirect and direct influence from Italian. They point out that

Spanish already had early alignment in narrow focus constructions, but that because of

accepted AM transcription is L+>H* and this is the one used throughout this dissertation (Estebas- Vilaplana & Prieto 2008).

72 convergence between the two intonation systems that are similar in other ways, “early peak alignment was dissociated from its pragmatic meanings (focus marker, emphasis) to become the default pattern in declaratives” (Colantoni & Gurlekian 2004:116). Early alignment is now the common pattern in Buenos Aires Spanish, even though Italian is no longer spoken in the community. Their conclusion that this change is contact-induced is supported by Barnes and Michnowicz’ (2013) findings regarding another variety of

Spanish in contact with Italian. Their study considers semi-spontaneous speech in the

Spanish of Chipilo, a small community in Puebla, Mexico, that is characterized by bilingualism with Veneto, a northern Italian variety. They find a majority of early peak alignment in Chipilo Spanish: 53% of peaks fall within the tonic syllable in pre-nuclear broad focus declarative contexts, which they argue is consistent with the hypothesis that the change is due to contact with Italian (Barnes & Michnowicz 2013:114). Although

Colantoni (2011:195) finds a higher rate of early peak alignment (80-100%), also in semi-spontaneous speech, both varieties exhibit a higher percentage of early peak alignment than what has been reported for non-contact varieties of Spanish. For example, in Peninsular Spanish, Garrido et al. (1995) find that the pitch peaks in the post-tonic syllable 70% of the time. In another study of Peninsular Spanish, also using read speech, speakers produce post-tonic peak alignment 80% of the time (de-la-Mota 1997). In spontaneous Castilian Spanish, Face (2003) find 75% late peaks. Rao (2005) reports an average of 64% post-tonic peaks for central Mexican Spanish in semi-spontaneous discourse.

The studies considered thus far have looked at Spanish in contact with a wide variety of languages, ranging from Basque (Elordieta 2003) to Quechua (O’Rourke

2005), and all have found influences from the other language on Spanish alignment, in all cases resulting in earlier alignment in pre-nuclear broad focus declarative contexts. The only exception to this trend is reported in Colantoni (2011), which finds that Spanish in contact with Guarani in Argentina exhibits post-tonic peak alignment. However, there is reason to think that change does not occur in this case because Guarani itself does not exhibit early peak alignment (Van Buren, Bittar, & Koops 2016, Bittar & Van Buren

2017). In other words, it seems reasonable to assume that early alignment does not occur because of contact itself; it occurs when the language Spanish is in contact with shares the early alignment pattern, which is also present in Spanish, only in other prosodic contexts (i.e. narrow focus and nuclear position). This could be due to reinforcement of a native pattern, resulting in indirect influence from the contact language (see Silva-

Corvalán 1994).

3.6.2 Spanish-English Alignment

English is a language characterized by alignment within the stressed syllable of pre- nuclear broad focus pitch accents. AM analyses of English claim that there is an H* associated with the stressed syllable of pre-nuclear broad focus declaratives, and the f0 peak aligns within the boundaries of the stressed syllable (Pierrehumbert 1980, Ladd

1996, among others).3 In a study of spontaneous speech, Girand (2006) analyzes 1,064 conversational English sentences and finds that combined, H* and L+H* make up 80.1% of pre-nuclear pitch accents. Similarly, Dainora (2001:86) analyzes the distribution of

3 Since there is ongoing debate about whether H* and L+H* in English are contrastive, I use L+H* as an umbrella for both (see Dainora 2001:119-121 for a discussion on the difference between the two pitch accents in English).

74 pitch accents in a subset of the Boston University Radio News Corpus, and finds 71% H* and 19% L+H* in pre-nuclear position. Furthermore, she finds only 1% of L*+H, the delayed pattern.

It should be noted that talking about English as if it were a homogeneous dialect is misleading, and studies have (not surprisingly) found dialectal variation in the specifics of alignment across English varieties. For example, Ladd, Schepman, White, May

Quarmby, and Stackhouse (2009) find later alignment in Scottish English than British

Received Pronunciation. Dalton and Ní Chasaide (2007) find alignment differences in three Irish English dialects. In an attempt to clarify whether there are pitch accent differences in English, Garding and Arvaniti (2007) look at three English pitch accents

(H*, L+H*, and L*+H) in Southern California and Minnesota speakers. While they do find differences in alignment between the two speakers, the differences are mainly in the pitch accent used for emphasis (L*+H), where late alignment does occur. On the other hand, in their analysis of the pitch accent L+H* produced when there is no emphasis, they find that speakers of both dialects align the f0 peak of the pitch accent L+H* around the middle of the accented vowel (Garding & Arvaniti 2007). Regardless of the particulars of variation, however, it can generally be stated that the English pattern is characterized by alignment within the accented syllable.

There appear to be no studies that directly compare this pitch accent in American

English with Spanish, but there has been a comparative study of Spanish with a single

British English speaker. Estebas-Vilaplana (2007) analyzes the phonological status of pre-nuclear accents in Castilian Spanish and British English by examining alignment patterns of the f0 peak in declarative sentences, taking into account the effects of

75 intervening unstressed syllables and duration of the stressed syllable. Although pitch accents in both languages are characterized by a rise, she finds that for her English speaker, the location of the f0 peak is consistently placed within the accented syllable, and the f0 peak of the Spanish speaker is consistently placed in the post-tonic syllable, although its placement is affected by stress and duration factors (Estebas-Vilaplana

2007:50). This leads her to conclude that the pitch accents are distinct phonological categories (H* for English and L* for Spanish with regards to the tone associated with the stressed syllable) (Estebas-Vilaplana 2007:53-54).4

Alvord (2006, 2010) is one of very few studies that addresses intonation in

Spanish varieties spoken in the United States. His study analyzes pitch accents in declaratives and interrogatives across three generations of Miami Spanish speakers.

Using Silva-Corvalán’s (1994) methodology for categorizing generations of speakers, he finds that there are no differences in alignment patterns of declaratives by generation.

That is, the generation born in Miami with one or more parents also born in Miami (3rd generation) exhibit the same patterns as the Cuban-born Spanish speakers (1st generation). Interestingly, he does find different usage patterns in the interrogative intonational patterns. The 3rd generation uses a rising pattern found in American English but not in Cuban Spanish, which leads Alvord (2010) to conclude that there is contact- induced innovation in Miami Spanish due to influence from English. Alvord (2010) does not analyze patterns in comparative contexts in the English of the bilinguals in his study, so it is unclear whether the pitch accents in their English declaratives exhibit early or late

4 Recall that the SpToBI convention for L+>H* was frequently L*+H until Estebas-Vilaplana and Prieto (2008). Therefore, although Estebas-Vilaplana (2007) concludes that L* is the associated tone for Spanish pre-nuclear pitch accents, this still corresponds to the L+>H* pitch accent.

76 alignment. This could make a difference, as findings in Robles-Puente (2014) suggest that the influence in alignment patterns may be from Spanish to English, rather than the other way around. Robles-Puente (2014) examines Los Angeles Spanish, which represents a variety situated within a heavily Hispanic community in the United States with roots in Mexican Spanish. Robles-Puente (2014:62) analyzes alignment patterns in pre-nuclear broad focus declarative pitch accents in the English and Spanish of the same speakers, and finds that the pitch overwhelmingly peaks within the post-tonic syllable regardless of the language being spoken. In other words, it appears that the prosodic system of the English speakers has been influenced by their Spanish. While their Spanish intonation does not seem to be affected by their English, Robles-Puente (2014) does find effects of English on Spanish rhythmic timing. Robles-Puente (2014:41) compares rhythmic patterns in the same bilingual speakers and finds that speakers who moved to

Los Angeles from Mexico at a young age have rhythmic properties distinct from monolingual Spanish speakers, an apparent English contact effect.

It may be that the differences in degrees of influence on the alignment of Spanish due to English in the different communities in the U.S. could be due to social factors, which are arguably more important than linguistic factors in contact situations

(Thomason & Kaufman 1988:35). In other words, the social factors in Miami may be amenable to intonational influence from English, but not in Los Angeles. However, there are also differences in influence related to the particular feature (e.g. rhythm vs. alignment in L.A. Spanish) and context (e.g. declarative vs. interrogative in Miami

Spanish) that must be taken into account. Romera and Elordieta (2013) found that L2

Catalan speakers adopted interrogative but not declarative patterns and attributed that to

77 the salience of the Catalan interrogative pattern. Therefore, salience seems to also be a factor regarding how susceptible a particular feature is to transfer.

The Spanish-English bilingualism in New Mexico has been more longstanding than in either Los Angeles or Miami. Speakers have generally held the view that English is prestigious and amenable to economic prosperity. Both of these factors (i.e. the length of contact and the status of each language) may contribute to the borrowing of English patterns into the Spanish of New Mexico. However, it is also clear that different levels of prosody may be influenced differently. The following section considers rhythm, and how this feature has been described for Spanish. In addition, this section discusses contact situations in which rhythm has been found to be susceptible to change, particularly in

Spanish-English bilingual settings.

3.7 Rhythm

Rhythm is an aspect of prosody that refers to the relative timing of durational elements in speech (Abercrombie 1967, Pike 1945). The perception of beats of heavy or light elements has to do with the patterns of syllables of prominence, and whether there is a greater difference in duration between stressed and unstressed syllables, as in English, or whether stressed and unstressed syllables are fairly similar, as in Spanish (Nava 2010,

Grabe & Low 2002). The difference has been described in terms of syllable-timing (e.g.

Spanish and Italian) and stress-timing (e.g. English and Dutch), which describe endpoints on what is now understood as a gradient continuum (Miller 1984, Dauer 1983). In other words, languages do not necessarily fall neatly into one category or the other, but rather pattern along a continuum between syllable-timed and stress-timed.

The pattern of syllables with roughly equal duration in stress-timed languages and of syllables with roughly equal duration in syllable-timed languages creates the perception of “Morse-code” beats in the former and “machine gun” beats in the latter

(James 1940). The difference between the two categories is displayed in

Figure 4 for English and Figure 5 for Spanish. These figures demonstrate that vowels tend to vary less in duration in Spanish and vary to a greater extent in English.

Figure 4. The English word ‘electricity’ spoken in isolation, demonstrating the high variability in duration across successive vocalic segments (i.e. in a stress-timed language).

Figure 5. The Spanish word electricidad ‘electricity’ spoken in isolation, demonstrating the low amount of variability in duration across successive vocalic segments (i.e. in a syllable-timed language).

The difference between stress-timed and syllable-timed rhythm is not categorical but rather represent points along a continuum. Nonetheless, differences are perceived by speakers. For example, Nazzi, Bertoncini, and Mehler (1998) presented newborns with languages belonging to different rhythm classes, and found that the newborns classified utterances according to rhythmic categories. Nazzi et al. (1998) presented the newborns with low-pass filtered speech retaining prosodic but not segmental information, and in two experiments the French newborns were able to discriminate between languages grouped by rhythm (Dutch and English, stress-timed vs. Spanish and Italian, syllable- timed) but not between mixed groups (Dutch and Italian vs. English and Spanish). In another study empirically demonstrating the perceptual categorization of stress-timed and syllable-timed languages, Ramus, Dupoux, and Mehler (2003) presented resynthesized speech data to adult French participants instructed to distinguish between two languages,

80 which they were told were exotic, made-up languages. The data were resynthesized to retain prosodic, but not segmental, information. Participants successfully discriminated between rhythm classes (for example, between English and Spanish) but were not able to discriminate languages that fall within the same rhythm class, for example between

English and Dutch.

The perception of rhythmic patterning results from temporal and structural characteristics of the language, including lengthening of stressed syllables, the reduction of unstressed vowels, and the phonotactics of the language. English exhibits regular vowel reduction in unstressed syllables, resulting in the perception of a stress-timing language (Nava 2010). In addition, syllable structure in English varies widely, resulting in syllables of unequal duration. Spanish, on the other hand, has less vowel reduction and less syllable structure variation (Ortega-Llebaria and Prieto 2007a). For example, CV is the most common syllable structure type in Spanish (Hualde 2005). In addition, Nava

(2010:89) finds that “stressed syllables are 50% longer than unstressed in English, whereas in Spanish that difference is only 10%”. Both of these qualities affect the placement of Spanish on the syllable-timed end of the continuum.

Various methods for measuring rhythm and prosodic timing have been put forth, with mixed results (see Arvaniti 2012 for a criticism of the methods discussed).

Nonetheless, the various measurements set forth capture a difference between English and Spanish. One of the frequently used methods is the Pairwise Variability Index (PVI), proposed by Low and Grabe (1995) as a way to measure durational variability across successive vocalic and intervocalic intervals. This metric assumes that duration is an acoustic correlate of rhythm that effectively captures rhythmic differences across

81 languages (Low et al. 2000). This method has since been replicated widely to compare rhythm in different language varieties (Asu & Nolan 2005 for Estonian, Barry, Andreeva,

Russo, Dimitrova, & Kostadinova 2003 for Italian, Gibbon & Gut 2001 for British

English and Nigerian English) and cross-linguistically (Grabe & Low 2002, Gibbon &

Gut 2001 for English and Ibibio, among others). The PVI is calculated by first taking the difference between the duration of consecutive vocalic or intervocalic segments of adjacent syllables. Then, the absolute value of the difference is calculated and divided by the mean of the segment durations. Dividing by the mean duration of the pair essentially normalizes the data for speech rate, a modification introduced in Low, Grabe, and Nolan

(2000). The nPVI (i.e. normalized PVI) score essentially calculates how similar consecutive segments are in duration. The score 0 represents no difference between successive segments, and the score 1 represents absolute difference. Studies who use the

PVI and similar metrics to analyze rhythm are essentially measuring durational variability of a segment (e.g. C or V) or larger prosodic unit and this is what is meant by rhythm and rhythmic variability.

A benefit of using the PVI metric to analyze rhythmic variability is the abundance of literature that facilitates comparisons of rhythm across languages and language varieties. Multiplying the PVI score by 100, White and Mattys (2007:508) report 36 as the nPVI-V (i.e. normalized PVI score for vocalic portions) score for Spanish and 73 for

English. Shousterman (2014:163) reports that .45 (or 45 if multiplied by 100) seems to be the approximate boundary between dialects of English that are perceived as more or less stress-timed; those below .45 are considered more "syllable-timed", and those above .45 more "stress-timed", which includes contemporary African American and European

English (based on Thomas and Carter's 2006 findings).

In an influential study, Low et al. (2000) investigated rhythm between British

English and Singapore English, since Singapore English is perceived as more syllable- timed than British English. They hypothesized that the perceived rhythmic difference between British English and Singapore English was accounted for by syllable duration. In

British English, vowel length differs depending on whether they are stressed or unstressed syllables. In Singapore English, on the other hand, vowel duration between stressed and unstressed syllable is more similar. Since vowel duration seemed to be an important factor in the perception of rhythmic patterns, their measurement took this into account. Low et al. (2000) found that the nPVI-V measurement revealed a difference in timing between Singapore and British English. Specifically, they found less durational variability between successive vowels in Singapore English than successive vowels in

British English, placing Singapore English as more syllable-timed than British English, as predicted.

Other studies have analyzed the effect of L1 rhythm on L2 production using the

PVI measurement, including Carter (2005), who considers the influence of Mexican

Spanish L1 on English L2 and finds that there is a substrate Spanish influence in the bilinguals’ production, which is rhythmically intermediate between North Carolina monolingual English and monolingual Spanish. Whitworth (2002) analyzes the rhythm of

English-German bilingual children and how their rhythm compares to the rhythm of their parents, who are native speakers of German (mothers) and British English (fathers). The

PVI measurement is able to capture fine-grained differences between English and

German, and shows that children pick up on the different patterns of their languages,

83 although not necessarily with native-like attainment (Whitworth 2002:202).

Other measurements quantifying rhythmic patterns have also been successful but are not without their own complications. Ramus, Nespor, and Mehler (1999) proposed a set of acoustic correlates of rhythm, which include ΔV, the standard deviation of vocalic intervals, ΔC, the standard deviation of consonantal intervals, and %V, the proportion of the utterance comprised of vowels. Ramus et al. (1999) argue that the best acoustic correlate of rhythm which captures rhythmic patterns effectively is %V. A key difference between this metric and the PVI is essentially the pairwise comparison. Ramus et al.’s

(1999) measure looks at a sample of Cs and Vs overall, or pooled within one prosodic phrase, but the result is not informative as to the variability across two adjacent syllables.

Several studies have compared the various rhythmic measures (e.g. PVI, ΔV, ΔC, and

%V, among others) and find that both interval measures and the nPVI metric captures rhythmic differences, although with respective strengths and weaknesses. White and

Mattys (2007) evaluate a range of rhythm metrics, including raw and normalized versions of PVI, and ΔV, ΔC, and %V, and apply them to languages classified as syllable-timed

(French, Spanish) and stress-timed (Dutch, English) in order to discern which metrics provide consistent discrimination between languages. They conclude that vowel-based formulas, in particular normalized ones such as nPVI, provide the most consistent and reliable discrimination between rhythmic classes (White & Mattys 2007:520). Low et al.

(2000) also compare the PVI to the metrics proposed by Ramus et al. (1999) and find that the PVI discriminates Singapore and British English most effectively, leading them to suggest that the PVI metric effectively captures variability across vocalic intervals, which is what sets apart rhythmic patterns in Singapore English from British English. Low et al.

(2000:395) admit that Ramus et al.’s measure ΔV (standard deviation of vocalic intervals) comes close to the PVI in capturing the difference between the language varieties.

As studies such as Whitworth (2002) and White and Mattys (2007) demonstrate, the PVI measurement provides a means to quantify rhythmic differences that are perceived by listeners. A benefit of using the PVI for analyzing Spanish in the U.S. is that this measurement has been used more commonly than other measurements, thereby facilitating comparisons (e.g. Thomas & Carter 2006, Carter 2005, Carter & Wolford

2016, Coggshall 2008, Shousterman 2014, Thomas & Ericson 2007). In these studies, the

PVI has effectively captured rhythmic differences both within varieties of a single language and across languages. Furthermore, the PVI formula has been used successfully in studies of conversational speech. For example, Thomas and Carter (2006) compare rhythm in African American and European American (Caucasian) English from North

Carolina in conversational speech. They also include as control groups rhythmic patterns of Jamaican English, L2 English with Spanish as the L1, and Spanish L1. Using the nPVI formula, they find that African American and European English are stress-timed, while

Spanish represents the syllable-timed end of the continuum, and Jamaican and Hispanic

English are intermediate between the two. Also using the PVI formula on conversational data (sociolinguistic interviews), Shousterman (2014) considers the possible substrate influence from Spanish on Puerto Rican English spoken in Spanish Harlem in New York.

She finds that the English of her speakers is relatively syllable-timed compared to the

African American and European American English speakers reported in Thomas and

Carter (2006). However, younger speakers (ages 15-30) show more variability across PVI

85 scores and are higher in general than PVI scores for older speakers (ages 45-60), indicating a possible shift towards more stress-timing (Shousterman 2014:167).

Regardless, Shousterman (2014) argues that maintaining syllable-timed English aligns speakers with other Latino Englishes and is a marker of their Puerto Rican identity, and distinguishes them from African American and mainstream U.S. English speakers.

Similarly, Coggshall (2008) finds that syllable-timed English is used as a marker of pan-

Indian identity by young Lumbee speakers in the Coastal Plain of North Carolina, where there is no known ancestral Native American language and no substrate influence is evident.

What is evident from these studies is that the PVI has been used effectively to compare rhythm across languages and within dialects of a language, rhythm can transfer across languages, and that speakers also make use of rhythmic patterns to mark identity.

3.7.1 Rhythm in Spanish-English Contact Situations

Because English and Spanish differ in rhythm type due to phonetic and phonological properties, situations of contact between speakers of both languages is ripe for research on prosody effects (e.g. Carter 2005, Shousterman 2014). Several studies have demonstrated that prosodic timing patterns can be transferred in both situations of long- term contact between Spanish and English (Thomas and Ericson 2007, Carter & Wolford

2016, Enzinna 2015), in newly formed bilingual communities, and in L2 speakers

(Thomas and Ericson 2007, Robles-Puente 2014). Thomas and Ericson (2007) look at rhythm in the English of two Mexican American communities: Pearsall in southern

Texas, with a long-established Mexican American population, and Raleigh, North

Carolina, characterized by a small Mexican American population currently experiencing growth. They compare the English of Mexican Americans in both regions with the

English of twelve Anglos from both states. Their study is interested in rising f0 prominence, the fronting of /o/, and prosodic timing, three features which are purportedly characteristic of Mexican-American English. Using the PVI formula on conversational speech, they find that the English of the Mexican Americans in both regions patterns similarly in that there is a greater degree of syllable-timing than in the English of the non-

Hispanics, which shows a greater degree of stress-timing (Thomas & Ericson 2007:200-

201). This suggests that Spanish can act as a substrate influence in the acquisition of

English, as the Mexican American speakers new to North Carolina demonstrate. The

Mexican American speakers are also differentiated from the Anglo speakers in their use of the intonational variable (rising f0) and fronted /o/, indicating that intonation and rhythm are useful as sociolinguistic variables much in the same way that segmental features are (Thomas & Ericson 2007:204). The Mexican American speakers in the sample produce a higher proportion of rising f0 pitch prominence than Anglo speakers in general, although younger speakers display more variability, as Shousterman (2014) found for rhythmic patterns of younger speakers in Spanish Harlem. In other words, younger speakers may be shifting toward a more English-like pattern in their rhythm.

Enzinna (2015) also looks at the effect of Spanish on English rhythm, comparing Miami

English monolinguals with simultaneous and sequential Spanish-English bilinguals. She uses Ramus et al.’s (1999) interval measures to test whether there is any prosodic influence from Spanish in the English of the community. Using data elicited from read speech, she finds that Miami English has acquired Spanish-influenced prosodic patterns

87 at a community level, leading to a more syllable-timed English (Enzinna 2015:113).

Studies examining the effect of English on Spanish in the United States are rare; regardless, existing studies have found English-influenced prosodic patterns. Carter and

Wolford (2016) focuses on a long-established bilingual community in South Texas that experiences little in-migration from Mexico. Their study examines rhythmic patterns in the English and Spanish of the same speakers across three generations. The speakers’ PVI scores are compared to a monolingual Spanish-speaking control group from Mexico, and there is a significant effect of group and language on PVI scores in the Las Alas community. Specifically, Carter and Wolford (2016:46) find that the rhythm of each age group in Spanish is significantly different from the rhythm of the subsequent age group, and that there is a change in each generation from more syllable-timed to less syllable- timed, so that the Spanish of the youngest speakers is the most stress-timed of all generations. Furthermore, PVI scores of the oldest age group are not significantly different from the monolingual Spanish control group. For the youngest speakers, there is no significant difference in prosodic timing between their English and Spanish. Thus, prosodic transfer has taken place in this community throughout three generations of

Spanish-English bilingualism. Prosodic timing in English has seemingly influenced

Spanish patterns, a result of convergence with English, according to Carter and Wolford

(2016:48).

In another study of U.S. Spanish, Robles-Puente (2014) examines prosody in Los

Angeles Spanish. This study considers both intonation (pitch accents) and rhythmic patterns of Spanish-English bilinguals. He hypothesizes that this particular contact situation could result in three possible outcomes regarding rhythmic patterns: the Spanish

88 rhythm could be more like English, the English rhythm could be more like Spanish, or the rhythm could fall somewhere in between monolingual norms (Robles-Puente 2014:4).

He finds that speakers with the most exposure to English present English-like rhythm in both their Spanish and English, characterized by more variability in successive vocalic segment durations. Likewise, he finds that speakers with the most exposure to Spanish

(newly immigrated Mexican Spanish speakers and bilinguals who moved to L.A. as adults) exhibit Spanish-like rhythm in both their Spanish and English. As described in the previous section, the results for the intonational variables were more complex. While rhythm seems to be highly susceptible to change in situations of language (and dialect) contact, intonation seems to be affected in more variable ways, a conclusion also drawn by Thomas and Ericson (2007).

It remains to be known, therefore, how different aspects of prosody are subject to change most quickly. Studies such as Robles-Puente (2014), Thomas and Ericson (2007), and the current study are therefore important for establishing whether there is a hierarchy of prosodic features in terms of their susceptibility to contact-induced change.

Distinguishing between specific prosodic variables and how they change individually in contact settings helps us to understand whether prosodic variables act similarly and should be treated homogeneously in studies of language contact and language acquisition

(see Matras 2007:39 for an example of this), or whether the susceptibility to change differs on the specific prosodic variable and the unique contact situation.

The current study also takes into account local pitch variability, since pitch range is an intonational feature reported to exhibit differences between English and Spanish.

The following section discusses this variable.

3.8 Pitch Range and Intensity

Alignment is one principal phonetic dimension on which pitch can vary, the other being pitch level, often called scaling (Ladd 2008:169). Whereas alignment is on the

“horizontal” time dimension, scaling represents the “vertical” dimension of pitch (Ladd

2008:188). Pitch range is one aspect of scaling. Specifically, pitch range is the amount that pitch changes throughout an utterance, possibly spread over multiple instances and calculated over some unit of time. A wide pitch range describes a high amount of pitch change in an utterance, and a narrow pitch range describes a low amount of pitch change in an utterance. A word can be uttered with the same tonal contour, such as rise-fall, for example, but can be uttered either with a higher peak and lower valley, or a valley and peak that are closer together on the vertical scale. Figure 6 displays a schema of an intonational contour that differs by pitch range, with Figure 6b wider than Figure 6a.

Figure 6. Schemas of two realizations of a similar pitch contour produced with different ranges.

Pitch range is a relative phonetic dimension; for pragmatic, physiological, and linguistic reasons, a speaker may expand or narrow their pitch range, and this affects the pitch contour, resulting in higher (or lower) points in the contour that proportionally affects other points in the utterances (Hirschberg & Pierrehumbert 1986:137). Similar to pitch

90 accents, focus and utterance type (e.g. declarative or interrogative) affect pitch range. For example, Willis (2002) finds an increased range in imperative productions compared to identical declarative utterances in Mexican Spanish. Frota (1998) finds differences in range depending on whether the focus is broad or narrow in European Portuguese. Pitch range plays a role in structuring discourse as well. Hirschberg and Pierrehumbert (1986) find that in English pitch range increases just after a major segment boundary in the discourse.

Pitch range also plays a role in how listeners evaluate attitude conveyed in an utterance. Even though there is a large amount of inter-speaker variability in pitch range

(Ladd 2008), it has been shown that there are features shared by a community. In other words, there are language-specific pitch range norms that listeners are attuned to.

German, for example, has been reported as having a narrower pitch range than English, and consequently, German speakers perceive English utterances characterized by a wider pitch range as aggressive (Gibbon 1998) and over-excited (Eckert and Laver 1994). In contrast, English speakers evaluate German speakers as bored or rude due to the narrower pitch range (Gibbon 1998). Building on these studies, Estebas-Vilaplana (2014) analyzes how pitch range differences are evaluated in English and Spanish, since these languages differ in terms of pitch range norms, with English speakers reportedly producing a wider range than Spanish speakers (see Estebas-Vilaplana 2009). The data in Estebas-Vilaplana

(2014) consisted of the word ‘mandarin’ and mandarina read by the same bilingual speaker, who actually produced the Spanish word with a narrower pitch range than the

English word. Pitch range was simply measured as the height of the f0 peak in Hz; the slope of the rise was also measured. After manipulating the words to vary in pitch range

91 by raising or lowering the peak by 28.2 Hz and keeping the slope the same, both English- speaking and Spanish-speaking participants in her study evaluated the utterances on the basis of politeness and attitude. English speakers listened to the English set and Spanish speakers to the Spanish set. As predicted, English speakers perceived utterances with a wider range as polite and “expected” (96.5%). On the other hand, 61.5% of utterances with a narrow range were evaluated as non-expected or rude. The results of the Spanish speakers were the opposite; 91.1% of utterances with a narrow range were evaluated as polite and expected, and utterances with a wider range were evaluated as rude, non- expected, or over-excited (83%) (Estebas-Vilaplana 2014:190-191).

Not only different languages, but varieties of the same language can exhibit differences in pitch range norms. Kvavik (1974) finds that pitch range in nuclear pitch accents differs between Peninsular and Mexican Spanish. Pitch range in Kvavik’s study is quantified as the distance in pitch from a local average. In Mexican Spanish, Kvavik finds a higher range represented in the final tone compared to Peninsular Spanish.

Colantoni (2011:192) reports on Buenos Aires Spanish, a variety historically influenced by contact with Italian. She does not acoustically examine pitch range but she cites researchers who suggest that range in Buenos Aires expanded due to influence from

Italian. This difference in range is supposedly salient to Spanish speakers of other varieties.

Anecdotal evidence abounds for pitch range differences across dialects and languages, but measuring such differences is not without its problems. Several studies show that global measures of pitch range, such as mean f0 across utterances, are not as effective as local measures for capturing differences in range as perceived by listeners

(Patterson & Ladd 1999). Patterson and Ladd (1999) had listeners judge utterances as being characterized by different adjectives such as expressive and irritated. They then measured pitch at local targets such as accent peaks, valleys, and sentence initial peaks and final lows, but also measured pitch globally, subtracting minimum f0 from maximum f0 across an utterance. Patterson and Ladd (1999) found that the local measures of pitch range correlated with judgments more effectively than the global measure. In a study attempting to quantify differences in pitch range between English and German, Mennen,

Schaeffler, and Docherty (2012) found that global measures did not convey position- sensitive differences between the two languages. Specifically, the anecdotal evidence that

German has more narrow pitch range than English was found to be a result of a compressed pitch range near the beginning of intonational phrases that expands in later parts of the phrase (Mennen et al. 2012: 309).

As mentioned, Spanish and English have been reported as exhibiting differences in pitch range patterns. García Lecumberri (1995) reports that English has a greater pitch range than Spanish and cites Navarro Tomás (1944), Stockwell and Bowen (1965), and

Cruttenden (1986) as work supporting the claim that pitch range is different in English and Spanish. Kelm (1995) quantifies average pitch range and standard deviation from the average pitch to test whether Spanish and English differ in pitch range as reported anecdotally. In his study, he elicits semi-spontaneous speech from native English speakers who are American college students and native Spanish speakers from Argentina,

Mexico, Panama, Peru, and Spain (Kelm 1995:437). He quantifies pitch range as the difference between the average high pitch and the average low pitch, and does not find a significant difference between Spanish and English. However, he finds that the amount of

93 variation in range, measured by the standard deviation of pitch from the mean every 30 ms is significantly greater in English than in Spanish. A higher standard deviation means more fluctuation in pitch, and a relatively small standard deviation means the pitch vacillates little throughout the utterances. Kelm finds that English speakers vary their pitch range more than native speakers of Spanish, and that the pitch range is narrower in the L2 of both Spanish and English native speakers than in their L1. The differences between global and local measures can account for why Kelm (1995) did not find a significant difference in range between Spanish and English, but rather found that local vacillations in pitch captured an effect for language.

Enzinna (2015), interested in whether Spanish has influenced Miami English prosody, uses Kelm’s methodology to analyze pitch range. Miami English is spoken by speakers who are not bilingual in Spanish and who have varying levels of exposure to

Spanish depending on neighborhood density of Hispanics and whether their parents speak

Spanish. She expects to find a smaller pitch range and standard deviation in Miami

English than in English spoken in Ithaca, New York, where speakers have had less exposure to Spanish. She also measures pitch range in bilinguals who learned English early and bilinguals who moved to Miami after childhood and learned English later. She finds that pitch range is indeed different in Miami English than Ithaca English. Enzinna

(2015:139) claims that Miami English speakers exhibit a pitch range characteristic of

Spanish-English bilinguals, quantified by having a lower f0 range and standard deviation than monolingual speakers in Ithaca, a difference that is significant. Also taking into account her finding that rhythm in Miami English is more syllable-timed than in Ithaca

English, Enzinna (2015) attributes the results to influence from Spanish. In sum, not only

94 have Spanish and English been shown to have different pitch range patterns, but this feature appears to be susceptible to change in bilingual and contact situations.

The PVI can also be used to measure f0 across consecutive vowels, which provides a local measure of pitch variability. Nokes and Hay (2012) use the pairwise comparison (PVI) to measure pitch variability in their study of New Zealand English, which they hypothesize has changed over time to be more syllable-timed than mainstream English. They use the PVI to measure pitch and intensity variation in vocalic segments across successive syllables in order to see whether there are concurrent changes in pitch and intensity along with vocalic duration. They find that over the 20th century,

New Zealand English has become more syllable-timed, as expected. Furthermore, duration has played less of a role in signaling stress, pitch and intensity have become more variable, thereby playing an increased role in signaling prominence in New Zealand

English. In addition, male and females use pitch and intensity differently to that end.

While the use of the PVI formula for dimensions other than duration has not been utilized frequently, the PVI was originally used to measure intensity variation across successive syllable (along with other acoustic correlates of prominence) (Low 1998). Since the PVI can measure variability in pitch across successive vocalic segments, the PVI should be sufficient to capture local variation in pitch. In addition, if durational variability is also measured using the PVI, pitch PVI can capture whether there are concurrent changes in pitch, facilitating a comparison of the role of different variables in prosodic change, as was evident for New Zealand English (Nokes & Hay 2012). Furthermore, intensity can also be measured within the same syllables as pitch and duration, giving a more complete view of prosody throughout time. The current study follows Nokes and Hay’s (2012)

95 methodology and utilizes the PVI to measure pitch and intensity variability across successive vocalic segments.

3.9 Conclusion

This literature review of prosody within the Autosegmental Metrical framework demonstrates that there are quantifiable acoustic dimensions of intonation and rhythmic timing that have been compared across languages and within language varieties, with promising findings. These phonetic dimensions provide an effective way to capture differences across languages such as English and Spanish (Kelm 1995, Enzinna 2015,

Carter & Wolford 2016, O’Rourke 2005, among others), and within a single language variety (see Nokes & Hay 2012). It has been shown that Spanish and English differ in peak alignment patterns, pitch range, and rhythm due to phonetic and phonological properties of the respective languages. These features represent quantifiable prosodic and intonational patterns that have been demonstrated to be susceptible to convergence. These findings suggest that such features may play a role in the unique prosody of NMS, a variety of Spanish in a long-term contact situation with English. Thus far, little attention has been paid to the influence of English on Spanish prosody and even less on prosodic change diachronically in Spanish in the United States (but see Alvord 2006, Carter &

Wolford 2016). The current study will contribute to the understanding of how prosodic patterns gradually change in a long-term contact setting, taking into account how sociolinguistic factors such as education level, exposure to Spanish, and socioeconomic status correlate with the amount and type of change. Furthermore, by considering different prosodic variables, this study will contribute to our understanding of the role of

96 individual prosodic components in contact-induced change.

Chapter Four: Methodology

4.1 Introduction The present study aims to analyze variation in prosodic phenomena in terms of pitch, intensity, and vowel duration in the speech of different generations of New Mexican

Spanish speakers who have experienced varying levels of English influence.

This chapter introduces the original design of the corpus used in this study, the details of the speakers that make up the corpus, how a subset of the sample was chosen for this study, and how the data were prepared for analysis. I then describe how I measured and quantified pitch peak alignment and variability in duration, pitch, and intensity using the acoustic software program Praat (Boersma & Weenik 2011).

4.2 History of the NMCOSS Data for this study come from the New Mexico-Colorado Spanish Survey (NMCOSS), which consists of 357 sociolinguistic interviews of speakers from New Mexico and

Southern Colorado. For a comparison with Mexican Spanish, the Spanish variety closest to New Mexican Spanish geographically and historically, I use pre-existing descriptions of Mexican Spanish intonation (e.g. de-la-Mota et al. 2010). For the current study, the main comparison of interest, however, is internal to the corpus; this study is interested in how intonation has either changed or remained stable across generations in New Mexico, and how the prosodic variables are conditioned by external variables such as education and Spanish and English language background. The corpus was designed in such a way that this type of analysis is possible.

Interviews for the NMCOSS corpus were collected in the early 1990s with the

98 goal of documenting the Spanish language as spoken in New Mexico and the southern third of Colorado at the end of the twentieth century (Bills & Vigil 1999, Bills & Vigil

2008). The corpus consists of interviews that took place in participants’ homes and various public locations, and interviewers were typically New Mexican Spanish speakers familiar with the participants and the local culture. One of the principal objectives for the creators of the corpus was to produce a linguistic atlas created from the lexical responses gathered in the interview (Bills & Vigil 2008:21). Therefore, it was essential to the principal investigators that the participants represent a balanced sample in terms of social and geographic distributions so that the data be a realistic sample of how Spanish was spoken in New Mexico and southern Colorado toward the end of the twentieth century.

Sixteen counties of southern Colorado were included because this region had originally been settled by northern New Mexicans and still had a relatively high Hispanic population (over 10%). With these objectives in mind, the area of New Mexico and southern Colorado was delimited into twelve sectors based on geography, population, and settlement history (Bills & Vigil 2008:22). For example, sectors 5, 9, 10, and 4 were the earliest to be colonized and roughly correspond to the Rio Grande drainage area. In the twelve sectors thus demarcated, over 355,000 persons above the age of eighteen reportedly used Spanish as a home language per the 1990 U.S. Census. Figure 7 below displays the distribution of sectors within New Mexico and southern Colorado as delimited by Bills and Vigil (2008). The dots represent areas where participants in the

NMCOSS are from.

Figure 7. Geographic sectors and locations targeted for the NMCOSS (Bills & Vigil 2008:23)

Sectors were furthermore broken down into localities, roughly one for every

5,000 Spanish speakers (Bills & Vigil 2008:24). Taking into account gender and age, one male and one female from each age group was selected from every locality, except for a few instances where this was not possible. The three age groups were young (18-39), middle-aged (40-60), and over 60. Socioeconomic factors were not considered as criteria for inclusion because the investigators claim that as a minority language, Spanish

100 variation in the region correlates weakly with socioeconomic status (Bills & Vigil

2008:25). In order to be included as a participant, consultants had to be adults who were born and raised in the region they represented. Additionally, consultants had to have acquired Spanish in the home during childhood to some extent (Bills & Vigil 2008:25).

Tape-recorded interviews consisted of three main parts and were designed to elicit a wide range of linguistic data in terms of regional, social, and stylistic variation: the first section elicited socio-demographic information from the participant, such as childhood residence, how many years of education he or she had, how many years of formal

Spanish education he or she had, and how often and with whom the consultant spoke

Spanish. The second portion consisted of specific elicitation of 800 items using pictures,

English translations, and verbal completion techniques. The pictures, real objects, and

English translations were meant to elicit lexical responses that could be easily compared; these formed the basis of the linguistic atlas. The verbal completion techniques were used to gather morphological, syntactic, and phonological phenomena (e.g. Tú le mandaste traerlo, y ayer ella lo __ ‘You ordered her to bring it, and yesterday she _____ it’ to elicit the preterit form of trujo/trajo ‘brought’). Interviewers were also expected to commence free conversation at specific points during this section. For example, after the group of lexical items relating to diseases, interviewers were prompted to start a conversation pertaining to local curanderos/curanderas ‘traditional healers’ and to medicinal plants used in their communities during childhood. The interview sessions ended with a brief reading in Spanish and a short conversation in English to assess bilingual proficiency.

Interviews ranged from one to eight hours in length with an average of three and a half hours. Due to the length and age of some participants (six consultants were 90 or older),

101 interviews were occasionally broken up into more than one meeting (Bills & Vigil

1999:47).

4.2.1 Subset of NMCOSS for current study

Because consultants in the NMCOSS were selected from the entire state of New Mexico and southern Colorado, the Spanish spoken represents a wide range of regional and social variation. Bills & Vigil (2008) were aware of this variation and were interested in distinguishing primarily between Traditional New Mexican Spanish and Border Spanish.

Traditional Spanish refers to Spanish transmitted from the early settlers who arrived pre- twentieth century. Border Spanish refers to the Spanish influenced by twentieth century immigration from Mexico, presumably a variety with close ties to the Spanish spoken concurrently in Mexico. Bills and Vigil (2008) established isoglosses and dialect boundaries between Traditional NMS and Border Spanish using participants’ first responses for specific lexical items. For example, a picture of a blouse could have elicited either cuerpo first, assumed to represent Traditional Spanish, or blusa, representing

Border Spanish (Bills & Vigil 2008:55). The main isogloss bundle between the two dialects is represented in Figure 8 below. The isoglosses in the map of the state of New

Mexico below delimits the main regional variation for eight lexical variables elicited in the interviews that distinguish between Border Spanish and Traditional New Mexican

Spanish.

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Figure 8. Map of New Mexico with Isogloss Bundle (adapted from Bills & Vigil 2008:320).

The major dialect split occurs between Valencia County and Socorro County. For the most part, speakers residing in counties north of Socorro County speak Traditional New

Mexican Spanish and speakers residing south of Socorro County speak Border Spanish, although there is considerable variability depending on the lexical item. There is also a bundle separating McKinley County from Traditional New Mexican Spanish. Because the current study is primarily interested in Traditional New Mexican Spanish, only speakers north of Socorro County are included, excluding participants residing in

McKinley County.

Sixty participants evenly distributed for sex and age were chosen for this study.

103

Participants were selected from the NMCOSS and were included in the study based on the following criteria: (1) speakers reside north of Socorro County and outside of

McKinley County, (2) speakers’ primary lexical responses to the eight items in Figure 8 place them as Traditional New Mexican Spanish speakers, operationalized as a majority of TNMS responses (i.e. at least five out of eight responses aligning with TNMS, such as salarata for ‘baking soda’), (3) the quality of the recordings allow for an acoustic- phonetic analysis of pitch (e.g. one young speaker was excluded due to frequent whispering throughout the interview), (4) the speaker learned Spanish before the age of

12, to ensure that only native Spanish speakers were chosen, and (5) there is enough conversational Spanish in order to extract a portion of continuous speech, essential for the quantitative analysis. From the resulting pool, thirty males and thirty females were chosen. Each gender was furthermore broken down to be evenly distributed for age. That is, males and females were divided evenly into the three age groups, with ages based on the same division as the original sampling for NMCOSS (Bills & Vigil 2008). This resulted in ten males and ten females in the young age group (ages 18-39), ten each in the middle-aged group (ages 40-60), and ten each in the older age group (61+). Only participants who resided in sectors 5, 6, 9, and 10 were included. These sectors were chosen based on settlement history (these are the four longest Spanish-settled sectors in

New Mexico) and geography, as the sectors surround the Rio Grande basin. The following figure displays where speakers grew up; blue dots represent speakers from urban areas and red dots represent speakers from rural areas, as categorized in the

NMCOSS metadata.

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Figure 9. Location where speakers in the NMCOSS subsample grew up, distinguished by urban or rural demographics.

In spite of the NMCOSS creators having age in mind when creating the corpus, there was a much larger number of older speakers than younger speakers. For example, there were

35 younger speakers who lived in the four chosen sectors, and 75 older speakers. When subsamples had to be narrowed further for my study (i.e. choosing 20 older speakers out of 75), speakers were chosen based on audio recording quality and highest number of

TNMS lexical responses from the eight displayed in Figure 8. Choosing younger speakers posed an even greater challenge. By the time interviews were conducted for this corpus (1991-1995), younger (and many in the middle-aged group) Traditional New

Mexican Spanish speakers were already English-dominant (see Bills & Vigil 2008:165), which is why Bills and Vigil (2008:165) considered this variety endangered. In the

NMCOSS, many participants struggled with expressing themselves in Spanish. In one

105 interview, for example, the interviewer completely switched to English halfway through the interview to be able to keep the interview going. Interviewees were given the option to speak in English or Spanish, and several chose English because they felt more comfortable speaking at length in this language. Ultimately, sixty speakers were chosen for the study who represent an even distribution between gender and age: 30 males and

30 females, split evenly into 10 young, middle-aged, and older speakers by each gender.

4.3 Independent Social Variables

The NMCOSS is a useful resource not only for the breadth of regional coverage, but also because of the extensive socio-demographic information collected for each participant, which include Spanish and English language background and socio-demographic factors.

Specifically, the social variables coded for in this study include age, gender, population

(to get at whether they grew up in an urban or rural environment), residence sector (5, 6,

9, or 10), years of education, years of formal study of Spanish, age learned English, age learned Spanish, Spanish language use (assessed by adding values for self-assessed amount of Spanish language use with co-workers and friends, with a maximum possible value of 10), and wealth (as assessed by the interviewer on the basis of house, furnishings, yard, automobile, and clothing, with a maximum possible value of 5). All variables and their values are taken from the categories coded for by the NMCOSS researchers and interviewers, except for population, which was obtained from the U.S.

Census (2010) and based on the residence where the participant grew up. Although the year is not ideal, 2010 was chosen because there was more information available in this year than in previous years for several of the small towns. Sector encodes the region

106 where the participant lived at the time of the interview; Sector 5 covers the Río Arriba region, including Santa Fe; Sector 6 covers the middle Río Grande Valley, including

Albuquerque; Sector 9 covers the area northeast of the Río Grande, including Mora.

Sector 10 is the most sparsely populated of the four sectors, and covers Mideast New

Mexico, including Torrence County and the large town of Santa Rosa. The independent social variables are summarized in Table 2 below.

Table 2. Social variables and their factors. Variables Factors Age Continuous, 18-95 Gender Female, Male Population 25-545,852 (input as log values 1.3617-5.7371 into statistical analyses) Sector 5, 6, 9, 10 Years of Education Continuous, 0-23 Years of Spanish Formal Continuous, 0-16 Study Age Learned English Continuous, 0-20 Age Learned Spanish Continuous, 1-12 Spanish Language Use Continuous, 1-10 Wealth Continuous, 1-5

Social variables are included as independent variables in the statistical analyses to test whether socio-demographic factors correlate with prosodic variation. However, for some variables, information was not available for all speakers; in such cases, the average value was taken from the input for all other speakers in the data set and given to the empty cell for that speaker. This was done for purposes of the statistical analyses only.

For example, two people had no information for Years of Education (YOE), and the average YOE value for all other tokens in the data was thirteen. For the two speakers and

107 their tokens, thirteen was added as their value for YOE. This process was necessary to conduct statistical analyses, otherwise there would be too many blank values across the board. For example, the speakers who did not have YOE input were not the same as the two speakers who did not have information for Age Learned Spanish. A summary of social variables by speaker is displayed below in Table 3. Blank cells indicate unavailable information.

Table 3. Participant socio-demographic and language use information.

Age Age Year Span Year Lear Lear s of ish s of ned ned Span Lang Int. Ag Gen Residence of Popul Educ Spa Eng Educ uage We # e der Sector Youth ation ation nish lish ation Use alth 1 52 F 6 Tomé, NM 1867 13 1 6 2 6 4 2 56 M 6 Tomé, NM 1867 12 1 6 0 5 4 3 52 F 6 Corrales, NM 8329 12 1 4 2 5 4 San José, Albuquerque, 54585 5 63 M 6 NM 2 16 2 1 -- 4 4 7 82 M 5 Chamisal, NM 310 17 1 7 1 6 -- 8 78 M 5 La Bajada, NM -- 4 1 6 0 7 2 9 29 F 6 Tomé, NM 1867 17 1 1 2 4 2 15 39 M 5 Chamita, NM 870 16 1 5 4 5 3 South Valley, Albuquerque, 54585 19 29 M 6 NM 2 16 3 1 6 4 4 Llano Quemado, 25 41 F 5 NM 2518 17 1 6 10 4 4 29 27 M 5 El Valle, NM 1440 17 1 3 5 1 4 South Valley, Albuquerque, 54585 32 34 M 6 NM 2 13 1 6 0 8 3 36 25 F 5 Córdova, NM 414 18 -- -- 3 5 4 Las Quebraditas, 37 40 M 9 NM -- 15 1 6 2 6 3 41 56 M 5 Córdova, NM 414 14 1 6 1 9 4 43 34 M 10 Pastura, NM 23 16 1 6 6 5 2 Armijo, Albuquerque, 54585 44 73 F 6 NM 2 4 1 6 0 6 2 50 74 M 6 San Luis, NM 59 12 1 8 0 4 4 63 29 M 10 Santa Rosa, NM 2848 16 3 1 14 1 4 67 45 F 5 Española, NM 10224 16 1 6 3 3 4

108

Guadalupe, Albuquerque, 54585 70 58 F 6 NM 2 13 1 10 0 5 4 Los Padillas, Albuquerque, 54585 73 66 F 6 NM 2 9 1 6 1 7 3 81 87 F 5 Abiquiu, NM 231 -- 1 6 -- -- 2 89 57 F 9 Las Vegas, NM 13753 12 1 7 0 6 3 91 44 F 5 Chamisal, NM 310 14 1 6 3 3 3 101 37 F 6 Algodones, NM 814 12 1 6 1 1 2 103 34 F 5 Española, NM 10224 12 1 -- 1 3 -- Barelas, Albuquerque, 54585 105 32 F 6 NM 2 10 1 6 2 2 4 107 56 M 9 Trujillo, NM 23 1 6 8 4 5 14417 108 83 F 5 Santa Fe, NM 0 16 1 1 6 -- 5 118 59 M 10 La Loma, NM 207 20 1 7 2 6 4 San José, Albuquerque, 54585 127 48 F 6 NM 2 11 1 6 0 3 5 142 80 F 5 El Valle, NM 1440 16 1 -- 7 3 3 144 83 M 5 El Valle, NM 1440 16 1 11 1 4 3 145 50 M 9 Pecos, NM 1392 12 1 -- 1 3 4 Los Griegos /Duranes, Albuq, 54585 152 29 F 6 NM 2 14 12 1 2 3 4 154 41 M 5 Questa, NM 1770 ------0 3 2 156 73 M 5 Costilla, NM 205 10 1 -- 0 10 3 157 38 F 5 Cerro, NM 428 13 1 -- 0 2 2 202 21 M 5 Gallina, NM 286 15 1 4 6 6 3 208 27 F 6 Bernalillo, NM 8320 17 3 1 16 4 3 La Jara/Cuba, 209 23 F 6 NM 207 16 4 1 3 2 4 214 76 M 9 Ojo Feliz, NM 90 4 1 20 0 6 -- 215 75 F 9 Cleveland, NM 820 16 1 6 2 3 3 220 23 F 9 Mora, NM 4881 17 1 1 1 4 3 221 27 M 9 Cleveland, NM 820 12 1 4 1 5 2 222 55 F 9 Mora, NM 4881 12 1 6 1 6 -- San Cristóbal, 230 44 M 5 NM 273 16 3 1 3 6 2 232 36 M 5 Chimayó, NM 3177 12 1 6 0 7 3 234 64 F 5 Valdez, NM 261 10 1 7 0 4 3 238 45 M 5 Embudo, NM 354 17 1 6 4 7 4 54585 241 73 M 6 Alameda, NM 2 8 1 6 0 3 3 246 76 F 5 Las Tablas, NM -- 7 1 6 0 3 3 271 79 M 10 Alamo, NM 1085 7 1 6 0 6 3 272 95 F 10 Santa Rosa, NM 2848 6 1 -- 0 5 1

109

279 59 M 6 Bernalillo, NM 8320 12 1 5 1 0 3 289 41 F 10 Vaughn, NM 446 12 1 -- 1 7 3 306 66 F 9 Springer, NM 1047 13 1 6 3 4 4 353 60 M 10 Santa Rosa, NM 2848 14 1 1 2 5 3 361 18 M 9 Ledoux, NM -- 13 1 1 1 4 3

4.3.1 Social Variables Hypotheses

Factoring in socio-demographic variables may elucidate the following research question, raised in Chapter 1: If NMS does exhibit change in apparent time, what socio- demographic and language use factors predict whether NMS speakers exhibit English- influenced Spanish intonational and prosodic patterns? In other words, what are the possible social driving forces behind intonational change?

The hypothesis put forth in this study is that younger speakers and those speakers with more English exposure are expected to produce more English-like prosodic patterns.

The apparent-time construct assumes that speakers reflect the norms of his/her community during adolescence (Meyerhoff 2011). Because the speakers in my sample have birth dates that span almost a century (between 1898 and 1977), and this period coincides with a societal increase in English dominance (Hudson et al. 1995), prosodic variation can be compared across speakers’ ages and Spanish language use, and from this, inferences can be made about possible change that has taken place. Therefore, the oldest speakers are assumed to reflect the norms of Spanish spoken in central and northern New Mexico at the turn of the century.

The following section describes how the samples were extracted from the corpus

110 and how the prosodic variables considered in this study were quantified and measured.

4.4 Data Analysis

4.4.1 Recording and Digitization

The interview audio files for NMCOSS were originally recorded on cassette tapes. The audio files have since been digitized onto CD files at a sampling frequency rate of 44 kHz. Original audio files were recorded in stereo format but were converted to mono format for this study. Once files were prepared for analysis, I selected a speech sample from each participant. Speech samples were five minutes long and contained relatively continuous speech by the interviewee.

For three speakers (ages 41, 41, and 56), it was only possible to obtain between three and four minutes of continuous speech. Although the NMCOSS interviews are long, the original objective was to obtain responses for lexical variants, and therefore it was possible to have a three-hour long interview with very few complete conversational phrases in Spanish, in particular if the interviewer chose not to follow the script and disregarded the conversational prompts. Regardless, five minutes was generally more than enough time to obtain enough tokens for the variables under analysis.

Care was taken to extract samples that covered similar topics to make samples as comparable as possible. Conversation about medicinal plants, curander@s ‘medicinal healers’, brujería ‘witchcraft’, death, wakes, and funerals was extracted if the sample was sufficient. If extracting conversation on this topic was not possible, then conversation regarding experience with Spanish and

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English was extracted, because this was a topic near the beginning of the interview that was present for nearly every participant. Both conversation topics also provided interesting examples of New Mexico folklife and experience. When choosing samples, I looked for no overlap with other speakers, reasonably coherent content, declarative utterances, longer phrases that contained pre-nuclear accents, and good acoustic quality.

After samples were extracted, I transcribed the speech into prosodic phrases in Praat (Boersma & Weenik 2011). Breaks between prosodic domains are cued by boundary tones along with a relative lengthening of the final syllable in the phrase and may be followed by a pause (Prieto & Roseano 2010). For my study, phrase boundaries were determined based on audible impressions and visual inspection of the spectrogram, mainly looking for lengthening and disjuncture, followed by a pitch reset. Once the samples had been transcribed in

Praat, I used the Praat plug-in Easy Align for automatic alignment of the transcribed speech sample (Goldman 2010). Easy Align segments the transcribed phrases into word-level, syllable-level, and phoneme-level boundaries. Using audio and visual cues in the spectrogram, the alignment of syllables and vowels for all samples was then corrected by hand. Precise annotation of syllables and vowels was essential for the PVI and f0 alignment analysis, the procedures of which are described in their respective sections below.

4.5 PVI Calculation

To calculate rhythmic timing, I used the vocalic normalized Pairwise Variability

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Index (nPVI-V) (as opposed to the raw consonantal PVI measure PVI-C), which is used to get at the difference in duration between consecutive stressed and unstressed vowels and is normalized for speech rate (Low et al. 2000, Grabe &

Low 2002). The difference between consecutive vowels is smaller in syllable- timed languages (e.g. Spanish) than in stress-timed languages (e.g. English).

Normalized PVI scores capture “the degree of durational variability in a set of acoustic data, measured sequentially, and it allows us to express numerically a tendency towards stress- or syllable-timing in one language or variety relative to another” (Low et al. 2000:378). nPVI scores are measured by calculating the mean difference between successive vowel pairs and normalizing for speaking rate (Low et al. 2000:383). The formula follows:

nPVI= (abs (Vowel A - Vowel B) / ((Vowel A + Vowel B) / 2)) x 100 (Low et al. 2000:383, using the more intuitive notation from Robles-Puente 2014:19)

Using this formula, higher nPVI scores indicate a more stress-timed prosodic timing, whereas a lower nPVI score indicates a more syllable-timed rhythmic timing, keeping in mind that scores are relative. Thomas and Carter (2006:339) argue that the PVI quotients are more informative in conversational speech when averaged out for all the measurements produced by a speaker, rather than averaged out utterance by utterance. I follow the same methodology.

Approximately 120 vowels were segmented for each speaker, resulting in an average of 107 pairwise comparisons per speaker. The number of pairwise comparisons is smaller than the number of vowels segmented because no comparisons were made across phrase boundaries. This resulted in a total of 6,370

113 tokens. Phrase-final feet were excluded (following Thomas and Carter’s 2006 methodology), and vowels were measured in consecutive phrases unless phrases did not have at least one pair of usable vowels (e.g. tal vez ‘Maybe’, depende ‘It depends’). In addition, phrases with disruptions in the audio (e.g. an airplane flying overhead, overlapping speech, etc.) and irregular speech (e.g. laughing, sneezing, etc.) were excluded. The phrase-final stressed syllable and all following syllables were measured, but not included in the nPVI calculation. This phrase- final foot was excluded to avoid including vowels with lengthening effects that typically occur in phrase-final position in Spanish (Prieto et al. 2010). If there was any doubt as to phrasal status, I considered there to be a phrasal boundary so that questionable syllables were not included in the calculation. Following the methodology of Thomas and Carter (2006:339), vowels in utterances where a restart or repair occurred were still considered, although the final foot was still excluded.

4.5.1 Segmentation Criteria for Vowels

The relevant segmental boundaries resulting from the automatic alignment were corrected by hand using guidelines outlined in Thomas and Carter (2006:340-343). Vowels were chosen for the pairwise variability comparison because vowels have been demonstrated to efficiently capture the perceptual differences in rhythm between languages and language varieties, and to be practical for conversational data when using the PVI method

(Thomas & Carter 2006:339). Segmentation first relied on spectral characteristics visible on a spectrogram using Praat’s default wide-band spectrogram settings. Waveforms were

114 used as a secondary source for fine-grained segmentation if needed, because waveforms show dips and rises in amplitude, corresponding to constriction onsets and releases (Turk,

Nakai, & Sugahara 2006:6). Auditory perception supplemented visual cues to determine boundaries between vowels and other segments, including adjacent vowels. Vowels were delimited using onset and offset of vowel formants as criteria. Specifically, onset and offset of F2 were cues of vowel presence. If further refinement was needed, periodicity in the waveform was used to determine changes in voicing indicating vowel presence. For voiceless stops, the oral closure and the brief period of aspiration following the burst, if present, were not included in the vowel. Glides, both preceding and following the vowel nucleus, were considered part of the vowel (e.g. guantes [ˈwan.tes] ‘gloves’, seis [sejs]

‘six’).

In Spanish, diphthongization and vowel deletion can occur across a word boundary when two vowels are adjacent to each other, such as in la escuela ‘the school’ (pronounced [les.ˈkue.la]), and such cases were also segmented as one vowel. Where hiatus occurred, vowels were segmented separately. Hiatus refers to adjacent vowels acting as separate syllables, such as in leo [ˈle.o] ‘I read’ and sabía [sa.ˈbi.a] ‘I/he/she knew’ and generally occurs when both vowels are non- high (e.g. /ao/ in ahora ‘now’) or when a stressed high vowel is preceded or followed by a non-high vowel (e.g. /ío/ in frío ‘cold’, /aí/ in caída ‘fall’) (Hualde

2005:77-79). Adjacent vowels are diphthongized if the sequence contains an unstressed /i, u/ adjacent to /a, e, o/ (e.g. /ia/ in italiano ‘Italian’, and /ai/ in vainilla ‘vanilla’). In many colloquial varieties of Spanish, including Mexican

Spanish (Hualde 2005:25) and New Mexican Spanish (Alba 2005), adjacent

115 vowel sequences that would otherwise be pronounced in hiatus are often realized as diphthongs or as a single vowel. Therefore, whether adjacent vowels were segmented as separate vowels was determined on a case-by-case basis. If vowels were determined to be in hiatus (i.e. phonetic reduction was not noticeable), visual cues in the form of changes in formant structure were used to determine boundaries between vowels. In such cases, two measurements were made.

Boundaries were then further corrected by listening to the audio to the left of the boundary and to the right of the boundary, so that at the point where the vowel to the left sounded distinct from the vowel to the right, the boundary was placed, in accordance with Thomas and Carter’s (2006:341) methodology. This type of fine-grained boundary marking also turned out to be necessary when segmenting vowels from intervocalic voiced stops, which are realized as approximants in Spanish (e.g. edad [eðað] ‘age’). As mentioned, the onset and offset of vowels were separated from surrounding approximants, nasals, liquids, and other surrounding consonants by visually inspecting the beginning and end of formants in the spectrogram, and by looking for periodicity within the waveform.

If formants were in transition, the boundary was segmented at the middle of the transition period. If vowels could not be reliably segmented, which occurred mainly due to disturbances in the audio (e.g. background noise, overlapping speech) or to exceptionally fast speech, then they were not included in the analysis, at which point the PVI chain was interrupted. See below on how such cases were treated in the PVI analysis.

After vowels were segmented on a TextGrid in Praat (Boersma & Weenik

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2011), a Praat script written by Christian Koops and modified by the author calculated the PVI scores. The script was run for each speaker individually, running through the speaker’s audio file and TextGrid. The script collected time points, individual vowel durations, and nPVI quotients for vowel pairs and returned the median and mean nPVI score for each speaker. The script exported information to a .txt file. A script was used to ensure consistency in measurements, as well as to facilitate future replication of the procedure.

Based on what is known about Spanish and English rhythmic timing, I hypothesize that the younger generation of NMS speakers exhibit higher nPVI scores than the older generation due to influence from English, and that as birth year increases, so too do the nPVI scores.

4.5.2 PVI: Pitch and Intensity

In addition to using the nPVI formula to measure variability in duration across successive vowels, I was also interested in variability indices for intensity and pitch to analyze how pitch and intensity varied locally across speakers. Languages exhibit differences in how various acoustic correlates of prominence are realized.

In addition to duration, increases in both pitch and intensity are associated with stressed vowels compared to unstressed vowels in Spanish (Llisterri, Machuca,

Mota, Riera, & Ríos 2003, Ortega-Llebaria 2006, Ortega-Llebaria & Prieto

2007b, Ortega-Llebaria & Prieto 2010). For the current study, the same vowels that were segmented for durational variability were used to measure variability in intensity and pitch using the PVI formula, following Nokes and Hay’s (2012)

117 methodology. PVI has been used to measure intensity in Low (1998) and to measure intensity and pitch in Nokes and Hay (2012). As noted by Nokes and

Hay (2012:5), “If prominence is created by language-specific bundles of prosodic variables, then a change in the rhythm profile of a language is likely to result not from the simple addition or subtraction of a variable, but from a more fluid shift in the weighting of the variables employed.” Therefore, if a consideration of change in rhythm and intonation is to be comprehensive, pitch and intensity should be measured along with duration, as they are also important variables affecting the perception of rhythm (Arvaniti 2009).

For the current study, to assess the intensity of individual vowels, the mean intensity across the vowel duration was calculated. For pitch, three different

PVI measurements were taken: mean, midpoint, and maximum f0. That is, each vowel was measured for mean pitch, the pitch at the midpoint of the vowel, and the maximum pitch in the vowel, and individual nPVI quotients were captured for each of these parameters. Nokes and Hay (2012:10) only calculated mean intensity and maximum pitch; I chose to include both mean and midpoint f0 for two reasons: (1) only considering f0 maxima may cancel out pitch variability in vowels that exhibit a rise or fall, and therefore taking together midpoint, mean, and maximum gives an idea of the behavior of pitch throughout consecutive vowels overall, and (2) since the PVI is a relatively innovative measurement of pitch range, it is unclear which of the measurements of pitch (f0 maximum, midpoint, or mean) more effectively capture pitch variability. The f0 was measured in ERB (Equivalent Rectangular Bandwidth), for two reasons: (1) this

118 measurement (compared to Hz and Semitones) seemed to be most informative for using the PVI formula in terms of outputting a more meaningful range of quotients, and (2) the ERB is an appropriate scale for capturing the perceptual differences in f0 (Hermes & Van Gestel 1991). For both intensity and pitch, PVI measures were normalized to account for local variation and to compensate in some way for the different ambient sound pressure levels (SPL) with regards to intensity due to different recording qualities.

A pitch object was created for every sound file with the purpose of performing a pitch analysis based on a cross-correlation method. A Praat script was created by the author and Christian Koops that analyzed pitch with a range of

75-300 Hz for males and 100-500 Hz for females, using standard Praat pitch settings. In vowels without periodicity, no f0 could be detected (resulting in an undefined value), and the vowel had to be discarded post hoc. Therefore, the overall number of tokens of pitch nPVI is lower than that of duration or intensity because of the presence of voicelessness. This is one difficulty that arises from using naturalistic data; a continuous pitch signal is rarely found in spontaneous speech, whereas in experimental studies with prepared and read speech

(containing as many voiced consonants as possible), a continuous pitch signal can be artificially enforced.

The script obtained measurements of the four parameters for each vowel

(i.e. mean intensity, mean pitch, maximum pitch, and midpoint pitch), and then outputted nPVI quotients for successive pairs of vowels, as well as outputting measurements for individual vowels. The script then exported information to a

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.txt file. In all, there are five PVI quotients for each speaker: duration, mean intensity, mean pitch, midpoint pitch, and maximum pitch.

Based on what is known about Spanish and English pitch range, I hypothesize that the younger generation of NMS speakers would exhibit higher

PVI scores for pitch than the older generation due to influence from English, indicating more local variability in pitch, and that as age decreases, the PVI scores increase. As for intensity, it is unclear how this variable will change; it is possible that if pitch and duration become more variable with age, as predicted, then the role of intensity in signaling prominence may decrease. It should be noted, however, that intensity is sensitive to recording procedure and recording conditions in the NMCOSS were far from ideal, though using the normalized PVI measure compensates in a small way (see Nokes & Hay 2012). Therefore, intensity is included as a preliminary investigation and findings may point to further research on how this variable should be treated in studies of New Mexican

Spanish prosody.

4.6 Peak Alignment

Alignment is a phonetic property which refers to the “relative timing of events in the f0 contour and events in the segmental string” (Ladd 2008:179). Studies such as Kügler (2004) on Swabian and Upper Saxon German and Atterer and Ladd

(2004) on Dutch, British English, and German show that measuring f0 in relation to segmental anchors such as syllable boundaries is an effective way to compare pitch across and within languages. With regards to the f0 peak alignment variable,

120 the current study is interested in the placement of the maximum f0 relative to the pitch accented syllable. Recall that the Spanish tendency in the pre-nuclear broad focus declarative pitch accent is for the f0 to peak in the post-tonic syllable (Prieto et al. 1995, Sosa 1999, Face 2002, inter alia). However, early peak alignment has been found in many contact varieties of Spanish (e.g. Colantoni & Gurlekian 2004 for Buenos Aires Spanish, O’Rourke 2003, 2005 for Cusco Spanish, Michnowicz

& Barnes 2013 for Yucatec Mayan Spanish, Elordieta 2003 for Basque Spanish), and researchers generally attribute this change to influence from the specific contact language (Colantoni 2011). In English, the f0 generally peaks within the tonic syllable in pre-nuclear broad focus declaratives (Silverman & Pierrehumbert

1990). The current study asks whether peak alignment patterns in NMS have been influenced by English patterns, considering peak alignment differs between

English and Spanish and alignment has been shown to be susceptible to transfer in contact settings (e.g. O’Rourke 2005).

For each of the 60 speakers in my sample, I extracted fifty tokens of pre- nuclear (i.e. non-phrase final) tonic syllables that received a pitch accent in a declarative utterance under broad focus. It was determined that the syllable received a pitch accent if it received prominence (a perceptual criterion) and if there was visible pitch movement within or surrounding the syllable. According to

Hualde (2002:5), “Typically (although not always), every lexically stressed syllable bears a pitch accent of some sort in a Spanish declarative sentence.” In other words, the analysis focuses on one structure corresponding to a single pitch accent, most often labeled L+>H* (Prieto & Roseano 2010), except in certain

121 contact varieties of Spanish (O’Rourke 2005, Elordieta 2003), that corresponds to the pre-nuclear broad focus declarative context.

How focus was operationalized requires explanation. Focus has to do with the information structure of a sentence, and this makes distinguishing between types of focus in conversational speech challenging. I attempted, therefore, to determine focus as consistently as possible, using the following guidelines from

Ladd (2008:213-215). “Broad focus” is a type of focus that is distinguished from

“narrow focus”. If the size of the focus constituent is larger than a single word, such as the sentence or verb phrase, then the utterance has broad focus. For example, in response to the question “What happened?”, the constituent that is in focus is the entire sentence, such as, “I went to the mall.” If, however, “I went to the mall” was a response to the question, “Where did you go?”, then the constituent in focus would be the noun “mall”, making this narrow focus.

Words with lexically stressed and pitch accented syllables that met the following criteria (in addition to being in pre-nuclear position and in broad focus declaratives) were segmented for analysis:

(1) the stressed syllable was not immediately followed by another stressed

syllable (e.g. the final syllable of también ‘also’ in the phrase también

múchos álamos ‘also many cottonwoods’, from Interview 15), for two

reasons:

(a) this avoids effects of tonal crowding that results in earlier peak

alignment in order to avoid clash (Arvaniti et al. 1998), and

(b) the calculation for maximum pitch might otherwise

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inadvertently consider the peak on the second stressed syllable to

be the peak for the first syllable, since both are considered together

under the procedure that searches for an f0 peak within the

temporal domain defined by both syllables;

(2) the final pitch accented syllable in an intonational phrase was also

excluded, as this was the nuclear pitch accent. That is, only accented

syllables in pre-nuclear position were considered;

(3) tokens with syllables that contained vowels pronounced with creaky

voice were also not considered. Creaky voice was determined by auditory

impressions and by a very low and irregular pitch track.

The first fifty tokens that fit these criteria from each sample of conversational speech were segmented manually in a TextGrid in Praat, both in full word and syllable sequences. If the stress on the word occurred in ultimate position (e.g. caminó ‘3p.sg walked’), then the following syllable was also segmented; for example, in caminó afuera ‘he walked outside’, both the tonic syllable of caminó

[no] and the first syllable of afuera, the unstressed [a], would be segmented. In other words, the two syllables that were segmented for the alignment calculation and relevant for the script described below were the tonic and post-tonic syllable.

Spontaneous speech makes pitch analysis challenging in various ways. For example, not all lexically stressed syllables exhibit a change in pitch. In such instances pitch may remain level throughout, with no visible rises or falls. Face

(2003) also found this in his comparison of spontaneous speech with laboratory speech. Voiceless consonants affect the f0 of adjacent voiced segments, and are

123 therefore avoided in experimental studies on peak alignment. Voiceless segments cause artificial peaks, either pre- or post-vocalically. In the current study, this problem is controlled for by coding for voiceless consonants and including the presence of a voiceless consonant as an independent variable in the regression analysis. Independent variables included in this study will be described in Section

4.6.2. Following is a description of how the dependent variable ‘peak alignment’ was measured.

4.6.1 Peak Alignment Measurement

The dependent variable was calculated as the temporal distance and relative position of the f0 peak to the offset of the tonic syllable. That is, peak alignment is defined here as the distance between the f0 peak and the end of the accented syllable. In order to demonstrate what is meant by this, a schematic accent shape and the corresponding tonal events is shown in Figure 10.

Figure 10. Measuring points at the f0 curve of the pre-nuclear rising pitch accent. (B= beginning of periodicity, E = syllable end, and M = f0 max).

Measurement of the accented syllable began at the commencement of voicing, including any voiced consonants in onset position (B) (Kügler 2004:89). In addition, measurements were taken of the f0 maximum of the rising pitch (M),

124 and the end of the stressed syllable (E). To normalize duration, the distance from

B to the f0 peak was divided by the total syllable duration, calculated as a percent of the total duration of the syllable. The formula is presented in 2 below (adapted from Kügler 2004:89). It is more typical in studies of Spanish alignment to measure the distance from the boundary in raw ms values (e.g. O’Rourke 2005,

Michnowicz & Barnes 2013). However, I chose this methodology (i.e. a normalized percentage) because comparing distance in ms is not informative when comparing across speakers, for whom speech rate differs greatly. A normalized value, on the other hand, is more comparable across speakers (i.e. a value of 75 means the f0 peak aligns 75% through the rime) and is easier to conceptualize.

Using this measurement, values above 100 indicate that the f0 peak is aligned within the post-tonic syllable, and values below 100 indicate that the peak is aligned within the stressed syllable. This is represented schematically in Figure

11.

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Figure 11. Example of the peak alignment measurement. If the pitch peaks in the post- tonic syllable, the value is over 100.

After fifty appropriate tokens were selected and the tonic syllable (commencing at voicing) and post-tonic syllable were segmented on a tier in a TextGrid, a script written by the author and Christian Koops calculated alignment scores over all segmented tokens of an individual speaker. Using the same guidelines as the pitch

PVI analysis, the script created a pitch object using the cross-correlation method with pitch range settings at 75–300 Hz for males, and 100–500 Hz for females.

The script obtained the following information which was exported to a .txt file:

Interview number, time at f0 peak, time the tonic syllable started and ended, the phrase the token occurred in, the segments making up the tonic and post-tonic syllable (e.g. /no.a/ for caminó afuera), and the alignment percentage value. The script also created a new point tier with a labeled point for each f0 peak. Below is an example of the TextGrid after the script has run through it.

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Figure 12. TextGrid from Interview 81 which shows the point representing the peak f0 within the tonic and post-tonic syllable of the word mismo ‘same’ in the phrase y al mismo tiempo ‘and at the same time’. Note that the alignment value is also added. The alignment value of 134.8 means that the f0 peak occurs after the offset of the stressed syllable, specifically after a temporal delay corresponding to 34.8% of the duration of the voiced portion of the stressed syllable (here, the /mis/ of mismo ‘same’).

Once the information for each token was collected from the script, additional independent variables were coded for by hand.

4.6.2 Independent Linguistic Variables in Peak Alignment Analysis

For each token, the following independent linguistic variables were coded for: Word

Class (verb, noun, adjective, adverb, function), Tonic Syllable Structure (open, closed),

Stress Position in Word (ultimate, penultimate, antepenultimate), Voiceless Segment

Present in Tonic Syllable (yes, no), Voiceless Segment Present in Post-Tonic Syllable

(yes, no), Intervening Unstressed Syllables (continuous), and Phrase Position (initial, medial). Function words were considered a factor for Word Class because occasionally function words such as para ‘for’ and una ‘a.FEM.SG’ received prominence and were therefore included in the variable context. The variable Intervening Unstressed Syllables refers to the number of unstressed syllables between the tonic syllable and the next lexically stressed syllable in the phrase. Recall that only tokens that were not immediately followed by a stressed syllable were considered. This variable has been shown to affect

127 alignment and was therefore included (Llisteri et al. 1995). The variable Stress Position was included as a way of coding whether peak displacement happens within- or across- words. In addition, stress placement has been shown to affect peak alignment in Spanish

(Prieto & Torreira 2007, Llisteri et al. 1995). Regarding coding for voiceless segments, there are two positions in each syllable (the tonic and post-tonic) that a voiceless segment could occur in: onset (e.g. padre ‘father’) and coda (revista ‘magazine). This variable was coded as ‘yes’ if the voiceless segment appeared in either position. For example, for the word padre with the stress on pa, the token would be coded as ‘yes’ for Voiceless

Segment Present in Tonic Syllable and ‘no’ for Voiceless Segment Present in Post-Tonic

Syllable. For the word revista with the stress on vis, the token would be coded as ‘yes’ for Voiceless Segment Present in Tonic Syllable and ‘yes’ for Voiceless Segment Present in Post-Tonic Syllable. Given that the most common syllable structure in Spanish is CV

(Hualde 2005), the voiceless segment appeared in onset position the majority of the time.

Furthermore, it appears that the artifacts caused by voicelessness raises the pitch following the voiceless segment. For example, in a word like seis, the edge of the first /s/ raises the pitch of the vowel onset more than the edge of the second /s/ raises the pitch of the vowel offset. The variable Phrase Position refers to whether the word containing the tonic syllable was in phrase-initial or phrase-medial position. The independent linguistic variables coded for are summarized in Table 4 below.

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Table 4. Independent linguistic variables and their factors Variables Factors Word Class Verb, Noun, Adjective, Adverb, Function Syllable Type Open, Closed Stress Position Antepenultimate, Penultimate, Ultimate Voiceless in Tonic Yes, No Voiceless in Post-Tonic Yes, No Intervening Unstressed Continuous Syllables Phrase Position Initial, Medial

The linguistic variables were included altogether in the multiple regression analysis with the social variables outlined in Section 4.3. Word, representing the specific lexical item containing the tonic syllable, was included as a random variable, due to an uneven distribution of words. In other words, the type token ratio is variable, as we would expect in naturalistic speech. To illustrate, there were 64 instances of the adverb cuando ‘when’ (the most common word in the data set) and one instance each of 658 words. In addition, because the behavior of individual speakers varies widely, ‘Speaker’ was included as a random variable.

Including a random effect within the regression analysis ensures that results are not the consequence of any single speaker, thus making the data more replicable and representative of the speech community rather than any individual speaker

(Johnson 2009). In the regression analysis, I also tested for pairwise interactions, for example between age and wealth, and gender and education.

Coding for voiceless segments present in the tonic and post-tonic syllable also makes it possible to do a secondary analysis excluding words containing voiceless segments. This makes the data more in line with experimental studies

129 that design phrases carefully to only contain voiced segments. In addition, several studies design tokens to only include peaks that are lexically associated with open syllables (Llisteri et al. 1995, O’Rourke 2005), as syllable type has been shown to affect alignment (Prieto & Torreira 2007, Kügler 2004). In naturalistic Spanish speech, it is difficult to find eligible tokens that contain voiced consonants only.

Regarding syllable structure, open syllables are easier to find, and are in fact the most common syllable structure in Spanish (75% in the current data). Since syllable type and voicelessness are coded for in this study, it is possible to include a conservative regression analysis that includes only tonic syllables with open syllables and voiced segments in the tonic and post-tonic syllable. In the dataset, there are 2,949 tokens which are included in the principal analysis. When tokens containing voiceless segments are excluded, the data set is reduced by almost two-thirds, to 1,134 tokens. When voiceless tokens and closed syllables are excluded, there are 972 tokens. In sum, there are two analyses, one with all tokens, and a secondary analysis with voiceless tokens and closed tonic syllables excluded. Furthermore, the principal analysis includes syllable structure and voicelessness as independent variables. That is, these qualities are controlled for when included in a regression analysis with other possible predictor variables, a common practice in both naturalistic (Barnes & Michnowicz 2013, Kügler 2004) and controlled studies of peak alignment (Prieto & Torreira 2007). The regression analysis then predicts the relative conditioning of the variables taken together on the realization of peak alignment.

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4.6.3 Alignment Hypothesis

Given the findings on peak alignment and the characteristics of Spanish and English in

New Mexico, I hypothesize that peak alignment patterns in NMS have been influenced by the increasing amount of bilingualism with English in New Mexico throughout the twentieth century. Specifically, I hypothesize that those speakers with more exposure to

English (i.e. younger speakers, those with more years of education, those from urban centers, and those with greater wealth) exhibit early peak alignment in pre-nuclear broad focus tonic syllables (i.e. f0 peak aligned within the tonic syllable), similar to English

(e.g. Silverman & Pierrehumbert 1990) and contact varieties of Spanish (e.g. O’Rourke

2003, Colantoni & Gurlekian 2004, Michnowicz & Barnes 2013), and unlike the late peak alignment pattern exhibited in Mexican Spanish and non-contact varieties of

Spanish.

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Chapter Five: Results

In order to answer whether Spanish has remained stable in New Mexico over the twentieth century in terms of prosody, or whether prosodic patterns in NMS have been influenced by prolonged contact with English, this study examines three main prosodic variables in New Mexican Spanish that are known to differ from English, a language the

New Mexican Spanish speakers have increasingly been in contact with throughout the

20th century: peak alignment, rhythmic timing, and pitch range. I begin with the results from peak alignment.

5.1 Peak Alignment

I hypothesized that New Mexican Spanish speakers would exhibit earlier alignment due to influence from English. This was not borne out in the data, however. In general, the pitch tends to peak in the post-tonic syllable in pre-nuclear position of broad focus declaratives in this variety of Spanish. The mean alignment value for all speakers in the study is 109.44. Figure 13 below presents an example of post-tonic peak alignment, in which the f0 for the word hermana ‘sister’ in pre-nuclear position rises throughout the stressed syllable ‘ma’ and reaches its maximum in the post-tonic syllable ‘na’, a pattern typical of monolingual Spanish. The vertical lines coincide with the f0 peaks. This pattern is the most common one found in the data.

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Figure 13. Declarative phrase mi hermana se quedó con todo ‘my sister was left with everything’ with post-tonic aligned peak in hermana ‘sister’. (Interview 44, 73-year-old female from Albuquerque)

The overall distribution of tonic and post-tonic peaks for all speakers in the study is presented in Table 5 below.

Table 5. Overall distribution of pre-nuclear f0 peaks. f0 % N Peak Tonic 43% 1257 Post- 57% 1675 tonic Total 2932 N

The majority of tokens are realized with a post-tonic f0 peak (57%), similar to what has been reported for Castilian Spanish and other, non-contact, varieties of Spanish, although not as high a percentage. Recall that Garrido et al. (1995) find a rate of 70%

133 post-tonic alignment in their Peninsular Spanish data consisting of read speech. De-la-

Mota (1997) finds post-tonic peak alignment 80% of the time, also in read speech in

Peninsular Spanish. Rao (2005) reports an average of 62% post-tonic peaks for Central

Mexican Spanish for all pragmatic categories in semi-spontaneous discourse. A summary of available percentages of tonic and post-tonic alignment in different varieties mentioned thus far are available in Table 6.

Table 6. Tonic and post-tonic alignment percentages as reported for different varieties of Spanish Language Variety Type of speech Tonic Post-tonic Alignment Alignment Peninsular Spanish (de- Read 20% 80% la-Mota 1997) Spontaneous Castilian Spontaneous 25% 75% Spanish (Face 2003) Peninsular Spanish Read 30% 70% (Garrido et al. 1995) Central Mexican Semi- 36% 64% Spanish (Rao 2005) spontaneous New Mexican Spanish Spontaneous 43% 57% (current study) Chipilo Spanish (in Semi- 53% 47% contact with Veneto) spontaneous (Barnes & Michnowicz 2013) Yucatan Spanish Spontaneous 64% 36% (Michnowicz & Barnes 2013) Buenos Aires Spanish Semi- 80-100% 0-20% (historically in contact spontaneous with Italian) (Colantoni 2011)

It should be noted that the data in my study were from naturalistic speech, and many of the studies on peak alignment in Spanish have been on highly controlled laboratory speech. In his study comparing alignment in laboratory speech to

134 conversational data, Face (2003:123) finds that earlier peaks occur more frequently in conversational speech. He finds 25% tonic-aligned peaks in broad focus declarative contexts, higher than the rate found in laboratory Spanish data. This rate (75%) of post- tonic peak alignment in spontaneous speech is still higher than that of the current study

(57%). However, it may be that Peninsular Spanish has a higher rate of post-tonic peak alignment than Mexican Spanish generally, as Rao found only a slightly higher percentage (62%) than that found in this study (57%). In her study of acoustic correlates of prominence in New Mexican Spanish, Benevento (2017:105) finds that out of all

‘accentable’ lexical items (including words such as yo ‘I’ and de ‘of’), 45% have early- aligned f0, and that late-aligned peaks make up only 23% of the data (n=146/324), although the data set includes all lexical items that could potentially be pitch-accented. Of the 324 tokens in Benevento’s data, roughly 28% were deaccented, that is, had no discernable pitch accent (Benevento 2017:112). The data in the two studies are therefore not entirely comparable (as mine only considered accented syllables), although

Benevento concludes that alignment in New Mexican Spanish falls within the expected range of variation for monolingual varieties of Spanish. The lower rate of delayed peak alignment found in my study compared to Face (2003), Garrido et al. (1995), de-la-Mota

(1997), and even Rao (2005) points to the same conclusion. Although lower than non- contact varieties, the rate of 57% delayed alignment in this study is still higher than the results reported in studies of contact varieties of Spanish, which generally report a majority early-alignment. For example, Colantoni (2011) finds between 80-100% early alignment in Buenos Aires Spanish, and Michnowicz and Barnes (2013:227) find 64% early peaks (or 36% late peaks) in spontaneous Yucatan Spanish.

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Regarding the results in the current study, one factor driving the number of tokens aligned within the tonic syllable (43%) is the high occurrence of tokens with an alignment score of 0. That is, the f0 in 393 tokens out of the 1257 tonic-aligned tokens

(31%) reached the peak at the very beginning of the voiced portion of the stressed syllable (i.e. have an alignment score value of 10 or less). Recall that the alignment value measures relative distance from the offset of the stressed syllable as a percentage, rather than distance in raw ms. A value above 100 indicates that the peak occurs after the tonic syllable, and a value below 100 indicates that the peak occurs within the stressed syllable.

A value of zero indicates that the peak occurs at the beginning of measurement, which would be the onset of voicing of the stressed syllable. See Figure 14 for a histogram displaying the distribution of all tokens in the data by alignment score.

Figure 14. Histogram of alignment score for all tokens in the data.

As the histogram shows, the distribution is bimodal, having two modes with a high frequency of alignment scores in the data. The first mode occurs near the beginning, indicating a high frequency of tokens with an f0 peak at or near the beginning of the voiced portion of the tonic syllable. The other center of variation occurs around 150,

136 indicating a high frequency of post-tonic peak alignment. To understand the alignment score better, Figure 15 displays a pitch track with the accompanying TextGrid that the

Praat script generates. The resulting TextGrid contains a point tier with the alignment score value for that token, as determined by the script.

Figure 15. TextGrid with alignment score point tier, from Interview 1

There are two pre-nuclear pitch-accented syllables in the phrase so lo estuvimos llevando como por tres veces ‘so we were taking him like for three times’ in Figure 15.

The accented syllables are vi in estuvimos ‘are.3pl.preterite’ and van in llevando ‘taking’.

Recall that the score is a value that measures the relative distance of the f0 peak to the end of the accented syllable and either the beginning of voicing of the stressed syllable or the end of the post-tonic syllable. This will depend on whether the f0 peaks in the tonic or post-tonic syllable. In the example provided in Figure 15, both tokens display rising f0 throughout the stressed syllable; in ‘estuvimos’, the f0 peaks two syllables after the

137 stressed syllable, although the measurement ends at the end of the post-tonic syllable

(thereby coinciding with the peak for that domain), and in the case of llevando, the f0 peaks late into the post-tonic syllable, producing the alignment score of 152.8, after which it dips and then rises again due to the voiceless consonant [k] in como.

Pre-nuclear lexical items with the f0 that rises through the tonic syllable and peaks before the boundary of the syllable also occur in these data, although infrequently.

Figure 16 below displays an example of a value below 100 that demonstrates a rise throughout the stressed syllable with an f0 peak before the end of the syllable.

Figure 16. TextGrid with alignment score point tier demonstrating early alignment, from Interview 2.

One reason for the high number of peaks with values below 10 is artificial f0 raising that is an artifact of voiceless consonants. You can see this in Figure 17, which outputted a value of 2.3 because of the artificial f0 peak from the voiceless [k] in cuarto

‘room’.

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Figure 17. TextGrid for the phrase Tenía un cuarto arriba en esa parte del techo ‘He had a room up there in that part of the roof’ from Interview 2. Notice that two tokens in this phrase have late alignment.

Laboratory studies of intonation generally avoid tokens and phrases with voiceless consonants, since in these cases the f0 track is discontinued and can artificially peak when transitioning into voiced segments. Furthermore, controlled studies tend to avoid closed tonic syllables (e.g. Llisteri et al. 1995, O’Rourke 2005), as syllable structure also interacts with peak alignment in that syllables with coda consonants tend to condition earlier peaks (Prieto & Torreira 2007:487). Table 7 displays the distribution of tokens in this study when voiceless consonants and closed tonic syllables are excluded.

Table 7. Overall distribution of pre-nuclear f0 peaks for open tonic syllables and voiced segments in the tonic and post-tonic syllables. f0 % N Peak Tonic 33% 652 Post- 67% 316 tonic Total 968 N

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As seen in the percentages in Table 7, when tokens containing voiceless consonants are thrown out, and only open tonic syllables are considered, the percentages are even more in-line with laboratory studies of alignment in non-contact varieties of

Spanish. That is, 67% of tokens have the f0 aligned within the post-tonic syllable, and

33% aligned within the tonic syllable, in pre-nuclear position. Furthermore, the mean alignment score becomes 123.44 (versus 109.44). Figure 18 displays a histogram of the distribution of tokens that include only open tonic syllables and voiced tonic and post- tonic syllables.

Figure 18. Histogram of alignment score for (C)V tonic and voiced tonic and post-tonic tokens in the data.

The distribution is still bimodal, even with voiceless tokens excluded. When examining this subset of the data, we find that 149 out of the 968 (15%) tokens have an

140 alignment value below 50. On further inspection, a common characteristic of such tokens is a pitch that is falling from a previous syllable, and that continues to fall throughout the tonic syllable. An example from the data is displayed in Figure 19.

The f0 in Figure 19 is at its highest in the first word, él ‘he’, and even though the subsequent syllable ha in habla is stressed and has the perception of being prominent when listened to, the f0 falls from the H on él into ha, where it subsequently rises again through bla, although at a reduced pitch range. Benevento (2017:73) characterizes this type of accent as H+L*, which she finds in her New Mexican Spanish data. She describes

141 this accent as having the f0 starting high and falling throughout the stressed syllable, generally reaching a valley around the syllable boundary (see Benevento 2017:194). This is the fourth most common pitch accent found in her sample (9%, n=28/324) of pre- nuclear broad focus declarative accents, preceded by H*+L (13%, n= 43/324), L+H*

(15%, 50/324), and L*+H (i.e. the delayed pattern) (23%, n=75/324). She describes the

H*+L accent as a “[f]alling tone that starts high at or near the initial portion of the tonic syllable and falls throughout the tonic syllable but never reaches a low tone valley within the syllable boundary” (Benevento 2017:194). This does not exactly describe what we see in Figure 19, however, as the valley does occur within the tonic syllable in this example. Regardless, it is possible that this accent accounts for a part of the low alignment scores; such an analysis should be examined in further research. Another interpretation is that there is a pitch accent on the previous word (here that would be él

‘he’) and that the prior pitch accent ‘bleeds’ into the analysis window. In other words, while tokens were excluded when the following syllable was also pitch-accented, the same is not true for the previous syllable. If we look closer at the first three syllables in

Figure 19, we see that there is a slight rise after the valley in [la], which then peaks in the post-tonic syllable [bla]. In other words, there seems to be a pitch accent on the first syllable of the phrase [e] which continues into the following syllable, and while there is an L+>H* pitch accent on [la], the peak is not as high as the initial pitch accent on [e].

What is of note here is that the histograms in Figure 14 and Figure 18 do not display a mode with a high occurrence of early peak alignment close to the boundary of the tonic syllable, suggesting that L+H* is not a common pitch accent in this sample of

New Mexican Spanish. Peak alignment tokens were also coded for various independent

142 variables, both social (external) and linguistic (internal). The data were then entered into mixed-effects linear regression analyses, one with voiceless tokens included and one with voiceless tokens excluded, in order to examine how various factors condition alignment when independent variables are controlled for. The results are explored in the following section. Social variables were not found to have a significant effect on alignment scores; hence, these variables will be discussed separately, after the results of the regression analyses have been presented.

5.1.1 Mixed Effects Linear Regression

The following seven independent linguistic variables outlined in Section 4.6.2 were entered into a mixed effects linear regression analysis: Word Class (verb, noun, adjective, adverb, function), Tonic Syllable Structure (open, closed), Stress Position in Word

(ultimate, penultimate, antepenultimate), Voiceless Segment Present in Tonic Syllable

(yes, no), Voiceless Segment Present in Post-Tonic Syllable (yes, no), Intervening

Unstressed Syllables (continuous), and Phrase Position (initial, medial). Eight social variables outlined in Section 4.3 were also included: Gender, Age, Sector, Log

Population, Years of Education, Age Learned English, Spanish Language Use, and

Wealth. In addition, two random variables (Speaker, Word), and six interactions between

Gender and Population, Gender and Years of Education, Gender and Age Learned

English, Age and Population, Age and Wealth, and Population and Years of Education were entered into a mixed-effects linear regression analysis using Rbrul (Johnson 2009) in the R statistical package (R Core Team 2016), with Alignment Score as the dependent variable. The variable Years of Spanish Education was not entered into the regression

143 because of an uneven distribution of values and this variable has a high level of multicollinearity with years of education. That is, speakers with more than four years of

Spanish study also have a high number of years of general education. Furthermore, Age

Learned Spanish is not included in the regression because of a highly-skewed distribution; a majority of speakers in this study learned Spanish at the age of 1

(n=55/60). However, both these variables and their distributions are discussed in the following section to give a comprehensive picture of the speakers in this study and their linguistic behavior.

This section will describe the results of the regression analysis, as well as discuss the linguistic variables that do not have a significant effect on alignment. The following section will describe the results of the regression analysis with voiceless segments and closed tonic syllables excluded. Finally, I will discuss the distributions of the social variables and how they pattern with alignment scores in Section 5.1.3.

A multiple regression analysis takes into account several independent variables at once and probabilistically models factors that can predict a distribution of the outcome. I used a step-down step-up model, which models the distribution both by creating a maximal model and then removing non-significant predictors, one at a time (step-down) and by creating a minimal model which adds each variable one at a time to test for significant changes in p-value (step-up). The ideal model is one where the outcome of the step-up and step-down matches.

Table 8 presents the results from the linear regression run in Rbrul. The model resulted in four significant predictors of Alignment Score: Tonic Syllable Structure (p <

.0001), Number of Intervening Unstressed Syllables (p < .001), Voiceless in Tonic

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Syllable (p < .0001), and Voiceless in Post-Tonic Syllable (p < .0001). All significant predictors of Alignment Score are linguistic factors, all of which have been well- established in previous studies as factors affecting the position of the f0 peak relative to the boundary of the tonic syllable. Reported at the bottom of Table 8 are (1) the total adjusted R2 value, which indicates the amount of variability explained by the regression model as a whole, (2) the AIC (Akaike Information Center), which measures how well the model fits the data and penalizes the model if there are too many variables; the smaller the number, the better the fit; and (3) the intercept, which provides a reference for the coefficients and for building the model predictions.

Table 8. Rbrul results for significant predictor variables on Alignment Score Multivariate Results Variable Level Coefficient Tokens Mean Tonic Syllable Type Open 13.633 2187 116.868 Closed -13.633 745 87.619 Intervening Unstressed Syllables Continuous: +1 4.324 Voiceless Segment in Tonic Syllable No 15.091 1615 125.25 Yes -15.091 1317 90.044 Voiceless Segment in Post-Tonic Syllable Yes 12.229 957 123.061 No -12.229 1975 102.834 R2 total =0.18, AIC = 33285.79, df = 8, Intercept= 97.59

The model explains 18% of the total variability of the data around its mean. This

145 is not high, and is possibly due to the non-normal distribution of the data.5

As can be seen in Table 8, four variables significantly predict the alignment score, and, subsequently, whether the peak is likely to be produced within the tonic syllable or the post-tonic syllable. The variables Voiceless in Tonic Syllable and Voiceless in Post-

Tonic Syllable have an effect in the expected direction: when there is a voiceless segment present in the tonic syllable, the alignment score is predicted to be significantly lower, with a mean of 90, which reflects the tendency for voiceless segments to artificially raise the f0. On the other hand, when there is a voiceless segment present in the post-tonic syllable, the alignment score is predicted to be significantly higher, with a mean of 123.

Recall that tokens were coded as having a voiceless segment present if the voiceless segment were either in onset or coda position, and the voiceless segment appeared in onset position the majority of the time. It should also be mentioned that the artifacts caused by voicelessness tend to raise the following f0, rather than the preceding f0 (e.g. in a word like seis, the edge of the first /s/ raises the f0 of the vowel onset more than the edge of the second /s/ raises the f0 of the vowel offset).

The coefficients for Syllable Type tell us that open syllables (e.g. casa [ˈkaˌsa]

‘house’) favor later alignment, with a mean of 116.868, and closed syllables favor earlier

5 An additional regression analysis was conducted on the data set when tokens with a score of 1 absolute deviation from the median (83.4) were excluded, a brute-force method of exclusion. This means tokens with an alignment score under 35.1 and over 201.9 were excluded. The alignment score mean increased to 125.367. The results were remarkably similar to the regression without such tokens excluded, except that Voiceless Segment in Tonic Syllable was not significant and one social variable became significant: Gender (p <.01). The coefficient for Female is 5.182 with a mean alignment score of 131.628; the coefficient for Male is -5.182 with a mean alignment score of 120.134. While males have an earlier alignment score, the score indicates that the peak is still firmly within the post-tonic syllable. In this analysis, the AIC is reduced to 19491.65, although still high, and the total R-squared is .171, even lower, indicating that the low R-squared likely results from the large standard deviations, that is, the scatter in the data overall. Excluding tokens one absolute deviation from the median is not common practice, so this analysis will not be given more consideration. It is provided, however, to illustrate how the regression results change when a portion of tokens are excluded. A more systematic way to overcome this problem is to conduct a separate analysis with voiceless segments excluded, which I present in the following section.

146 alignment (e.g. culpa [ˈkulˌpa] ‘fault’), with a mean of 87.619. The box plot in Figure 20 displays the distribution for alignment score by Syllable Structure.

Figure 20. Box plot for Alignment Score by Syllable Structure

Barnes and Michnowicz (2013:116) also found an effect of Syllable Type in their study of naturalistic speech in Chipilo Spanish, although in the opposite direction. In their results, open syllables favored earlier alignment than closed syllables. However, other studies have found the opposite effect (i.e. presence of a coda conditions earlier alignment) (e.g. Prieto & Torreira 2007, García 2016). Although Barnes and Michnowicz

(2013:116) suggested that the differences in the findings between their study and Prieto and Torreira’s could be due to the difference between laboratory and natural speech, the findings in this study suggest that naturalistic speech patterns similarly to laboratory speech with regards to this variable.

In the current study, Number of Intervening Unstressed Syllables also reached significance, similar to Alvord (2010) but again unlike Barnes and Michnowicz (2013).

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The coefficient for Intervening Unstressed Syllables displayed in Table 8 shows that for every additional intervening unstressed syllable, one can expect the alignment score to increase by an average of 4.324, with the intercept as a basis. The scatter plot in Figure

21 displays the distribution of token alignment scores by how many unstressed syllables follow the pitch-accented syllables. Note that the regression line has a positive slope.

Figure 21. Scatter plot of data distributed by Number of Intervening Unstressed Syllables.

The linguistic variables that do not have a significant effect on alignment in the model are

Word Class, Stress Position, and Phrase Position. Each of these will be discussed individually below.

Word Class. The raw distribution of mean alignment score by Word Class is displayed in Table 9 below. Figure 22 is a box plot that visually shows the distribution of alignment score by grammatical word class.

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Table 9. Mean alignment score by variable Word Class Word Class Mean Alignment N noun 114.28 788 adjective 112.86 309 verb 110 1320 adverb 93.32 300 function 105.82 215 Total N 2932

Figure 22. Box plot of alignment score distribution by Word Class

Even though Word Class is not significant in the regression, when looking at the raw data we can see what appears to be a big difference between some of the levels. In particular, adverbs have an earlier alignment than other word classes. For example, as

Table 9 shows, adverbs have a mean alignment score of 93.32, whereas nouns, with the highest alignment score, have a mean of 114.28. What is it about adverbs that the peak aligns so much earlier, and why did Word Class not reach significance with such a high difference in group means? The answer likely resides in a single word that is driving the

149 mean down: cuando ‘when’. Out of 300 adverbs, 63 instances are of cuando, and the mean alignment score for this word is 23.8. The word also occurs in initial position 34 times (53% of all its occurrences). It can be speculated that cuando tends to have an earlier alignment score because it begins with a voiceless segment, the tonic syllable

/kuan/ has closed syllable structure, and it tends to occur at the beginning of a phrase with the pitch at its maximum height. The influence of this single word on group means is controlled for by having ‘Word’ entered as a random variable in the regression. For a complete list of the random effects of Word and Speaker, see Appendix A.

Stress Position. The raw distribution of mean alignment score by Stress Position is displayed in Table 10 below. Figure 23 is a box plot that visually shows the distribution of alignment score by Stress Position in the word containing the pitch- accented syllable.

Table 10. Mean alignment score by variable Stress Position

Stress Position Mean Alignment N antepenultimate 133.44 71 penultimate 109.70 2505 ultimate 102.78 356 Total N 2932

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Figure 23. Box plot of alignment score distribution by Stress Position

Clearly, the farther back (to the left edge) in the word the stress, the later the alignment.

Llisterri et al. (1995) found a similar effect in that penultimate stress conditioned post- tonic alignment over words with other stress patterns. For the current study, an

Approximative K-Sample Fisher-Pitman Permutation Test analysis was conducted to test whether there are any statistically significant differences between group means. The test resulted in a significant difference in mean alignment score between group means (chi- squared = 9.8559, p < .01). When individual levels are compared against each other in a

Wilcoxon rank sum test (non-parametric U-test), it turns out that the significant difference is between Antepenultimate and Penultimate (W=105150, p < .01), and

Antepenultimate and Ultimate (W=15838, p < .001). When pitch-accented words have

151 antepenultimate (e.g. último ‘last’) stress, the alignment is much later than when the word has stress in ultimate position (e.g. españól ‘Spanish’). Even though group means differ greatly from each other, this variable does not significantly predict alignment score in the regression analysis, when all variables are considered together.6 This may also be a case where having ‘Word’ as a random variable in the regression analysis controls for the influence exerted on group means by a few words that act differently than other words of the same type. In addition, the effects of this variable may be overshadowed when other factors are considered in the regression analysis, such as Intervening Number of

Unstressed Syllables. It is also noteworthy that out of 356 words with ultimate stress, 134 are closed syllables (38%), which is known to condition earlier alignment. Compare this to 2,505 words with penultimate stress, only 600 of which are closed syllables (24%).

Therefore, the effect of ultimate position and earlier alignment may actually be a result of syllable structure.

Phrase Position. Finally, Phrase Position is the third linguistic variable that does not reach significance in the regression analysis. I discuss this variable further in the following section, where it is found to have a significant effect on alignment score when voiceless segments were excluded. At this point, I will give a brief description of the distribution of alignment score by Phrase Position (initial or medial) in a raw table of means (Table 11) and box plot (Figure 24).

6 In an alternative analysis, this variable was coded as a continuous variable such that the variable was ‘distance of stressed syllable from word edge’ with ‘ultimate’ as 1, penultimate as 2, and ultimate as 3, with the hypothesis that peak displacement is more likely within the domain of the word, and the closer the stressed syllable to the word edge, the more the peak will remain within the word. However, even when entered into the regression as a continuous variable, there was no significant effect of stress from distance to the right edge of the word.

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Table 11. Mean alignment score by variable Stress Position Phrase Position Mean Alignment N initial 102.2923 887 medial 112.5346 2045 Total N 2932

Figure 24. Box plot of alignment score distribution by Phrase Position

Pitch-accented syllables that occur in words in phrase initial position have a lower alignment score (102.29) than words in medial position (112.53). In a Welch two sample t-test, the difference in means between initial and medial phrase position is significantly different (t = -3.4029, p < .001, 95% confidence interval between -16.15 and -4.339). By contrast, O’Rourke (2004:334) found that for Cusco speakers, early peaks occur more frequently in medial position (verbs in her constructed examples) than initial position

(subjects). Since O’Rourke found the opposite effect and since this variable did not reach significance in this analysis, it is possible that the difference seen here (i.e. earlier

153 alignment in initial position) may be an artifact of the noise that accompanies naturalistic data. However, this variable reaches significance in the regression analysis in which voiceless segments are excluded and will be discussed further in the following section.

5.1.1.1 Regression Results Including Continuously Voiced Syllables

It is clear from the results of the mixed-effects regression analysis that the presence of voiceless segments in the tonic and post-tonic syllable affects peak alignment. Laboratory studies of peak alignment and f0 avoid voiceless segments for this reason. While excluding voiceless segments in naturalistic data is impractical, by coding for the presence of voiceless segments, we not only control for the conditioning factor of voicelessness, but with enough tokens, we can also attempt to exclude such segments. An alternative methodology is to exclude a certain percentage of the vowel from measurement to avoid artificial f0 effects from voicelessness or obstruents. However, excluding tokens with very low alignment scores (as I did in the previous section) accomplishes the same purpose.

In order to make the data in this study more comparable to laboratory studies, a second analysis was conducted with voiceless tokens and closed tonic syllables excluded.

Doing so follows the practice of Michnowicz and Barnes (2013), who analyze alignment in spontaneous Spanish speech and also present two separate analyses for the same reason. In the current study, the second analysis included 968 tokens, with the exact same set of internal and external independent variables as the larger analysis, with the exception of the independent variables Presence of Voicelessness in either syllable and

Tonic Syllable Type, which now no longer applied. The rationale behind this analysis,

154 other than creating a subsample of the data that is structurally more like laboratory

Spanish alignment studies, is that it is possible that the first model does a poor job in

‘regressing out’ the effect of voicelessness. In other words, the noise that is introduced by voicelessness could drown out relevant social effects that are actually there in the data.

The results of the mixed-effects regression analysis with voiceless tokens and closed tonic syllables excluded using Rbrul (Johnson 2009) in the R statistical package

(R Core Team 2016) are displayed in Table 12. Two variables are significant: Intervening

Unstressed Syllables (p < 0.001) and Phrase Position (p < 0.001)

Table 12. Rbrul results for significant predictor variables on Alignment Score when tokens with voiceless segments and closed tonic syllables are excluded Multivariate Results Variable Level Coefficient Tokens Mean Intervening Unstressed Syllables Continuous: +1 6.374 Phrase Position Initial -7.482 352 113.616 Medial 7.482 616 129.053 R2 total =0.084, AIC = 10759.68, df =6, Intercept= 108.182

The overall alignment score mean for tokens in which the tonic syllable is open, and all segments in the tonic and post-tonic syllables are voiced is 123.439, higher than when voiceless segments are included. There are two differences between these results and the results from the larger regression analysis: Phrase Position is now significant (p <

.001) and the effect of Intervening Unstressed Syllables is higher (although it reaches significance in both).

Although the mean alignment score for both initial (113.616) and medial position

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(129.053) indicates that the peak is delayed either way, there is a large difference between them. Words in initial position are predicted to have significantly earlier alignment than words in medial position. This is unexpected, given that O’Rourke

(2005:80) finds the opposite direction of effect for her Cusco speakers; that is, alignment is latest in initial position, earlier in medial position, and earliest still in final position.

However, O’Rourke (2005:79) does not find a significant difference in alignment between words in initial and medial position for her Lima speakers, that is, the speakers with the least community-wide exposure to Quechua. There is another study that finds the same direction of effect as O’Rourke’s (2005) Cusco speakers. Fant (1984:30) finds that the f0 peak location is different in phrase-initial and phrase-medial H* accents in

Peninsular Castilian Spanish; whereas the f0 peaks at the end of the tonic syllable in phrase-medial words, the peak is delayed in phrase-initial position. That is, the peak is later in phrase-initial position. Since the direction of the effect found in the current study is different from that in O’Rourke (2005) and Fant (1984), this may reflect a difference in intonation between laboratory and natural speech. That is, perhaps in natural speech words in phrase-initial position have earlier peaks than words in phrase-medial position.

However, this is not entirely intuitive, as it could be argued that tonal crowding from the boundary tone of the previous phrase would condition later alignment in initial position.

This variable will have to be examined more in studies of conversational speech in order to understand its effect on alignment in natural speech. Regardless, it should be kept in mind that when tokens with voiceless segments and closed syllables are present in the regression, then this effect does not reach significance, suggesting that when the effects of voicelessness and tonic syllable structure are controlled for, position of the word in the

156 phrase does not significantly predict the alignment score.

5.1.2 Social Variables

Recall that the social variables considered in the current analysis are Gender, Age, Sector,

Log Population, Years of Education, Age Learned English, Spanish Language Use, and

Wealth. The variables Years of Spanish Education and Age Learned Spanish are also coded for but not entered into the regression analysis because of an uneven distribution of data points. No social variables reached significance in the regression analysis, but it is worth considering how alignment score was distributed across variables, in particular age and Spanish/English language use variables. Table 13 displays the mean alignment score for the discrete external factors. Note that age was entered into the regression as a continuous variable, but is shown here in discrete groups as a way to conceptualize alignment score by age.

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Table 13. Mean alignment score for discrete social variables Variable Mean Standard N Alignment Deviation Score Gender Female 110.44 80.36 1447 Male 108.45 71.43 1485 Age Group Younger (18-39) 107.13 79.3 967 Middle (40-60) 116.01 78.11 977 Older (60+) 105.19 69.87 988 Sector 5 (Río Arriba 106.59 78.22 1111 region, inc. Santa Fe) 6 (middle Río 112.81 76.04 924 Grande Valley, inc. Albuquerque) 9 (Northeast of 108.67 74.13 548 Río Grande, inc. Mora) 10 (Mideast 110.76 71.12 349 NM, inc. Torrence County and Santa Rosa)

The difference in mean alignment score by gender is slight, and does not appear to interact with other variables; recall that Gender was tested for interactions with

Population, Years of Education, and Age Learned English based on observing various cross-tabulations.

When age as a continuous variable is tested for a correlation with alignment score in a non-parametric correlation test, the result is non-significant (Spearman’s rank correlation rho = 0.0045, p = .40). However, using a non-parametric ANOVA test, the K-

Sample Fisher-Pitman Permutation Test, there is a significant difference in group means among Younger, Middle, and Older age groups (chi-squared = 11.299, p < .01). When

158 individual levels are compared against each other in a Wilcoxon rank sum test (non- parametric U-test), it turns out that the significant difference is between Middle and

Younger, and Middle and Older. Table 14 displays the results of the tests.

Table 14. Output of Wilcoxon rank sum tests for the variable Age Group Age Age Mean Mean W p-value 95% Confidence Group Group Score Score Interval (x) (y) (x) (y) Lower Upper Bound Bound Younger Middle 107.13 116.01 444020 *0.0219 -13.1001 -0.6999 Older 107.13 105.19 480760 0.8062 -4.6001 5.9999 Middle Older 116.01 105.19 447640 **0.0054 -14.8000 -2.2001 * The mean difference is significant at the .05 level **The mean difference is significant at the .01 level.

Whereas the original hypothesis of this study predicted that pitch alignment scores would decrease as birth year increased, indicating a change in apparent time toward earlier alignment due to influence from English, these data clearly do not support that. In fact, the age group with the earliest alignment are the oldest speakers, although the difference in means is not significantly different from the younger speakers. It is unclear why the Middle speakers (ages 40-60) would have the latest alignment. One possibility is that this age group has more influence from Mexican Spanish, rather than

English. One thing is clear, however: all three groups exhibit post-tonic alignment, and are exhibiting clear “Spanish” patterns.

The group differences in mean for Sector are not significant. Unfortunately, the distribution among regions is not balanced, with there being 23 speakers and 1111 tokens representing Sector 5, which includes the Rio Arriba region of New Mexico (e.g. Santa

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Fe, Córdova, and Española), and only seven speakers and 349 tokens representing Sector

10, a sparsely populated region which includes small towns such as Santa Rosa and

Vaughn. It may be that in order to get at regional differences in intonation in New

Mexican Spanish, which there surely are, a more in-depth analysis comparing a few towns in each region must be undertaken.

This study also questioned whether speakers living in urban or rural environments would exhibit differences in alignment, possibly due to greater (and earlier) exposure to

English in more urban environments. It was decided to enter population in as a continuous variable, since the cut-off for “urban” is somewhat arbitrary in New Mexico, where the most urban city in Sector 10, for example, is Santa Rosa with a population of

2,800 in 2010 (U.S. Census 2010). In order to be able to compare locales with raw numbers, population had to be converted into log frequency in order to avoid a comparison between very low values, such as 23 (population of Pastura, NM) and extremely high values, such as 545,852 for Albuquerque, NM. See Figure 25 for a scatter plot of token alignment scores by population in log values.

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Figure 25. Scatter plot of token alignment scores by population in log values.

The correlation between alignment score and population is not significant in the regression analysis, and furthermore, the correlation displayed in Figure 25 is not in the direction we would expect, based on the hypothesis. The trend displayed in these data is that the greater the population, the higher the alignment score. We may speculate that the higher alignment scores in urban environments may be due to more exposure to Mexican

Spanish in highly populated areas. Again, this possibility of a change, not towards

English-like patterns but towards Standard Spanish-like patterns, may be a likely explanation for what is happening in New Mexican Spanish and will be explored in

Chapter 6.

Figure 26 displays scatter plots with regression lines for the remainder of the continuous social variables: Years of Education, Years of Spanish Education, Age

Learned English, Age Learned Spanish, Spanish Language Use, and Wealth.

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Figure 26. Scatter plots for the remainder of the continuous social variables: Years of Education, Years of Spanish Education, Age Learned English, Age Learned Spanish, Spanish Language Use, and Wealth.

While the regression line has a positive slope for Age Learned English and appears to represent a correlation, there is only one speaker who learned English at age 20 (Speaker

214, mean alignment 129.914) who is likely responsible for driving the mean up as age learned English increases. Therefore, with Speaker entered as a random variable in the regression analysis, the effect of this single speaker is controlled for and the variable Age

Learned English is not found to have a significant effect on alignment.

Spanish Language Use has a negative slope, indicating a decrease in alignment with greater Spanish use. This would be contrary to what is expected, since greater

Spanish Language Use means that participants are using Spanish to communicate with friends and coworkers, and we would expect stability of patterns in this case. However, this would again seem to be the effect of a single speaker driving the effect down.

Participant 156, a 73-year-old woman from Costilla, has the only Spanish Language Use score of 10. She also has a mean alignment score of 82.5. Therefore, by inserting Speaker as a random effect in the regression analysis, the influence exerted by this speaker is controlled for. Regression lines for Years of Education, Years of Spanish Education, and

Wealth are rather constant, suggesting a weak effect for these variables on alignment score.

The results of the current study are similar to Alvord’s (2010) Miami Cuban

Spanish study in that late alignment in pre-nuclear declarative utterances appears to be a robust feature of this community that is not susceptible to change from English patterns.

In other words, alignment is consistent across different social factors in this sample, and

163 there are no clear patterns of variation along social dimensions. This points to the lack of apparent-time change in peak alignment in New Mexican Spanish.

5.1.3 Peak Alignment Results Summary

In the main regression analysis, Syllable Type, Intervening Unstressed Syllables,

Voiceless Segment in Tonic Syllable, and Voiceless Segment in Post-tonic Syllable are found to have a significant effect on alignment score. In the secondary regression analysis with voiceless segments excluded, Syllable Type, Intervening Unstressed Syllables, and

Phrase Position are found to be significant. Only linguistic (internal) variables significantly predict alignment score, regardless of whether all tokens are included in the data set, or only those with voiced segments are present. Therefore, there is no evidence for change in progress or for social variation of peak alignment in this variety of Spanish.

Therefore, peak alignment does not appear to be influenced by English or the amount of

English exposure participants have had, nor does this appear to be a variable that contributes to the unique prosody of New Mexican Spanish, as the alignment values are similar to what has been reported for other, non-contact and mainstream varieties of

Spanish (e.g. Prieto et al. 1995, Navarro Tomás 1918, Hualde 2002, Sosa 1999, Face

1999, 2001, 2002).

5.2 Durational PVI

The method used in this study to measure rhythmic timing is the Pairwise Variability

Index (PVI), created by Low and Grabe (1995) to compare variability across the duration of successive syllables. Recall that PVI scores indicate the relative degree of syllable-

164 timing or stress-timing, with higher scores indicating more stress-timed (English-like) and lower scores indicating more syllable-timed (Spanish-like), because a higher score indicates more variability between successive syllable nuclei. This study uses the same methodology to measure PVI as Thomas and Carter (2006) and Carter (2005), both of which look at the vowel nucleus of syllables in naturalistic speech and use nPVI-V, which normalizes for speech rate. Their results provide an external baseline to compare

Spanish and English for this study. Carter (2005) found that European Americans

(English monolinguals from North Carolina) had a PVI of .5304, Hispanic English speakers .4264, and Spanish speakers (combined monolinguals and bilinguals from

Mexico City and Colima, Mexico) .2798. The PVI of the Spanish of the bilingual speakers ranged from .2762-.3127, and the English of the bilingual speakers ranged from

.3596-.4447 (Carter 2005:70). These ranges are the speaker means, rather than the ranges of the tokens themselves, which are much wider.

The measurements in this dissertation study resulted in 6,370 PVI comparisons produced by 60 speakers. The mean PVI for all speakers in this study is 0.3604, median

0.3045, with a standard deviation of 0.2737. The range of speaker mean PVIs is 0.273-

.444, a wider range than Carter’s (2005) Spanish bilinguals. In fact, the values at the high end (reaching .444) are within the top range of the English of Carter’s (2005) bilinguals.

While the PVI scores are higher than the Spanish speakers in Carter’s study, they are comparable to White and Mattys’ (2007:508) finding of 36 (multiplying the PVI score by

100) score for their Spanish speakers and 73 for their English speakers (the study does not provide information on the speakers’ origins). Therefore, the PVI scores for the NMS speakers are situated within the norm for Spanish monolingual speakers. Table 15 lists

165 the mean PVI scores for the different studies considered. Figure 27 displays the distribution of all tokens in the current study.

Table 15. Mean PVI scores in Carter (2005:70), White and Mattys (2007:508), and the current dissertation study Group Mean PVI Carter (2005) European American .5304 English Hispanic English .4264 Spanish (monolingual and .2798 bilingual) Spanish of Bilinguals .2762-.3127 English of Bilinguals .3596-.4447 White and Mattys (2007) Spanish .36 English .73 Current Study Spanish PVI Mean .3604 Mean PVI range .2730-.4440

Figure 27. Histogram of PVI scores for all tokens in the data.

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The distribution is right-skewed and shows that the majority of tokens have a PVI around

0.36, but that there are extreme values toward the high end of the PVI index. The box plot in Figure 28 shows the outliers in the data, 90 in total. Outliers were kept in the data set, as they were determined to be good data points that reflect actual variability in the data.

For example, Figure 29 displays a TextGrid with vowels marked off for analysis, and one can see the difference in duration between the second and third vowels is large (0.11477 ms) and results in a PVI score of 1.177. These differences occur in the data and should not be excluded. Note in the TextGrid that the final foot is labeled “F”, and not included in calculations.

Figure 28. Box plot of PVI values in data set

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Figure 29. Example of high variability in successive vowels, Participant 232, 36-year-old male from Chimayo.

This study is interested in whether there has been a change in rhythm patterns throughout the twentieth century due to increased influence from and bilingualism with

English. With a mean PVI of 0.3604, speakers in these data are closer to Carter’s

(2005:70) Spanish speakers (.2798) than to his non-Hispanic English speakers (.5304).

The mean of the NMS speakers is also the same as the Spanish speakers in White and

Mattys’ (2007) data. In other words, the rhythm of this sample of New Mexican Spanish speakers is firmly on the Spanish end of the continuum. However, the range of PVI speaker means is higher in this sample (.273-.444) than the Spanish of Carter’s bilinguals.

In fact, the range is as high as the English of Carter’s (2005) bilinguals (although that is arguably low for English – recall that Shousterman (2014:163) reports .45 to be the approximate boundary between dialects of English that are perceived as more or less stress-timed, and those below .45 are considered more syllable-timed). Therefore, the rhythm of the NMS speakers is considered relatively syllable-timed and within the norms for Spanish.

The following section presents the results of the mixed-effects linear regression

168 analysis that tests for the effects of social variables on PVI. Finally, Section 5.2.2 explores the distribution of PVI scores across various (non-significant) social variables.

5.2.1 Regression Analysis

Eight social variables (Gender, Age, Sector, Log Population, Years of Education, Age

Learned English, Spanish Language Use, Wealth), five interactions (Gender and Years of

Education, Gender and Wealth, Gender and Age Learned English, Age and Wealth, and

Gender and Age), and one random variable (Speaker), were entered into a mixed-effects linear regression analysis using Rbrul (Johnson 2009) in the R statistical package (R Core

Team 2016), with PVI as the dependent variable. Selected interactions were chosen based on observing patterns within cross-tabulations of data during exploratory analysis. The data set included 6,370 tokens of PVI comparisons (average 106.2 tokens per speaker).

The regression analysis resulted in one significant effect on PVI scores: the interaction between Gender and Years of Education (p <.001). Table 16 presents the results from the linear regression in Rbrul. See Section 5.1.1 for information on how to read the linear regression output. It should be noted that the results are from the Step-

Down regression; the Step-Up regression resulted in no significant effects.

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Table 16. Rbrul results for significant predictor variables on Alignment Score. Multivariate Results Mean Variable Level Coefficient Tokens vif Gender Male 0.045 3103 0.362 Female -0.045 3267 0.359 Years of Education (YOE) Continuous: +1 0.001 Gender:YOE Female +1 0.003 >10 Male +1 -0.003 >10 R2 total =0.01, AIC = 1600.362, df = 6, Intercept= 0.343

The significant interaction between Gender and Years of Education indicates that as females gain more education, their PVI score increases, whereas with males, the mean

PVI is consistent regardless of years of education. Raw PVI means for females and males distributed by years of education are displayed in Table 17. The interaction is displayed in Figure 30, in which it is evident that males and females exhibit different behavior with regards to years of education.

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Table 17. Mean PVI scores for females and males by Years of Education. Years of Females Males Mean Education 4 0.3175 0.3832 0.3615 6 0.3347 - 0.3347 7 0.3626 0.3807 0.3713 8 - 0.3630 0.3630 9 0.3484 - 0.3484 10 0.3241 0.3520 0.3333 11 0.2920 - 0.2920 12 0.3617 0.3721 0.3665 13 0.3707 0.3490 0.3636 14 0.3256 0.3285 0.3270 15 - 0.3875 0.3875 16 0.3530 0.3651 0.3600 17 0.3969 0.3572 0.3777 18 0.4111 - 0.4111 20 - 0.3085 0.3085 23 - 0.3520 0.3520 Total 0.3587 0.3622 0.3604

Figure 30. Interaction plot displaying mean PVI scores for females and males depending on years of education

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Females with 11 years of education or fewer have low PVI values, with an average of

0.3299. Females with more than 11 years of education, on the other hand, have an average PVI of 0.3698. The average PVI for males with 11 years of education or fewer is

0.3697, and for males with more than 11 years of education the mean PVI is 0.3525.

Males vary little across the board regarding years of education with no clear-cut patterns.

Females, on the other hand, clearly have higher PVI scores the more years of education.

In general, females have a lower mean PVI (0.3587) than males (0.3622). However, if females with more years of education can be significantly predicted to have higher PVI values, then there may be an association with higher PVI values and prestige, and women may be sensitive to this association.

The other socioeconomic variable coded for in this study is Wealth, and while it is not a significant predictor of PVI values, it too has a similar pattern as Years of

Education in that females with increased wealth have higher PVI values. Mean PVI values for Wealth by Gender are displayed in Table 18, and the interaction plot for

Gender and Wealth is displayed in Figure 31.

Table 18. PVI means for females and males distributed by years of education. Wealth Females Males Mean 1 0.3347 - 0.3347 2 0.3441 0.3835 0.3637 3 0.3539 0.3620 0.3583 4 0.3773 0.3529 0.3662 5 0.3260 0.3520 0.3349 Total 0.3587 0.3622 0.3604

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Figure 31. Interaction plot displaying mean PVI scores for females and males depending on wealth.

This pattern of increasing PVI with wealth for females has an exception, when the rating is 5, in which case the PVI declines abruptly. There are only two females with a rating of

5, one with a mean PVI of 0.359 (Participant 108, an 83-year-old from Santa Fe), and one with a mean PVI of 0.292 (Participant 127, a 48-year-old from Albuquerque), who is clearly driving the mean down for the 5 rating. This is one example why Speaker entered as a random variable is essential. The mean PVI scores for males, on the other hand, steadily decline with more wealth.

5.2.2. Non-significant Social Variables

The variables that did not reach significance in the regression analysis are Sector, Age,

Population, Age Learned English, Spanish Language Use, and Wealth. Although these

173 variables did not reach significance in the mixed-effects regression analysis, it is still worth considering how PVI means were distributed across variables, in particular age, as the main research question asks whether there is a change in PVI across ag as a reflection of increasing English influence.

My hypothesis predicted that as age decreases, PVI scores would increase to more closely approximate English PVI values. Table 19 below provides the raw PVI scores for speakers in this study broken down into age groups, in addition to the number of comparisons for each group and the standard deviations. Figure 32 is a box plot that shows the IQR distributions for the three age groups, and Figure 33 compares the age groups in a bar plot.

Table 19. Statistical Information for speakers broken down by age group Age Group N Mean PVI Std. Deviation Younger 1978 0.3710 0.2820 Middle 2254 0.3564 0.2686 Older 2138 0.3548 0.2712

Figure 32. Box plot of PVI distribution by age group.

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Figure 33. Bar plot of PVI distribution by age group.

As predicted, younger speakers have the highest PVI (0.3710), although the differences across groups is slight. I conducted an ANOVA and a correlation test to establish whether there are significant differences among age; an ANOVA tests the differences in group means among Younger, Middle, and Older, and a correlation test inputs age a continuous variable and tests whether there is a positive or negative correlation between age and PVI. In the Approximative K-Sample Fisher-Pitman

Permutation Test (ANOVA for non-normally distributed data), the differences in group means are not significant (chi-squared = 4.3223, p = 0.1147,). However, the correlation test (Kendall’s rank correlation tau) with age as a continuous variable finds a significant negative correlation between PVI scores and age (z = -2.1112, tau = -0.0179, p < .05,). In other words, the older the speaker, the lower the PVI. Figure 34 provides a scatter plot of all PVI measurements for speakers distributed by age and contains the regression line demonstrating the negative slope.

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Figure 34. Scatter plot of PVI results by age

When PVI speaker means are plotted by age, as is depicted in Figure 35, it is easy to see the relationship between age and PVI. The graph plots the mean PVI score (y-axis) for each person analyzed in this study by age (x-axis). In other words, each point represents the mean PVI score for an individual. As is shown, younger speakers have higher PVIs, indicating more stress-timed rhythmic timing than older speakers.

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Figure 35. Individual mean PVI scores plotted by age. The red line is the regression line. The blue line is the LOWESS (Locally Weighted Scatterplot Smoothing) line.

While there is a significant effect for age, and it is in the expected direction, the difference remains slight. In addition, the effect size is small, smaller than expected based on the results of Carter and Wolford (2016), who find in the small Mexican-American community in Texas that the Spanish of each generation is significantly more stress- timed than the previous generation. Furthermore, this variable did not reach significance in the linear mixed-effects regression analysis, and therefore, the effect is possibly controlled by factoring in other independent variables and by including Speaker as a random effect.

Regarding gender, it is well-known that males and females pattern differently during linguistic changes in progress (Tagliamonte 2011, Labov 1990). In particular,

177 young women tend to be at the forefront of language change, and women also tend to be more sensitive to prestige norms (Tagliamonte 2011:32). I would expect that if the vernacular pattern in NMS is a lower PVI (more Spanish-like), and a change would be toward higher PVI scores, then women would have higher PVI scores indicating more durational variability across successive vowels than men. In fact, women have a lower

PVI score than men in this sample. The difference, however, is very slight. Table 20 provides the mean PVI scores and standard deviations for males and females in this study. The distribution of PVI scores by gender is displayed in the box plot in Figure 36

Table 20. Statistical Information for speakers broken down by Gender Gender N Mean PVI Std. Deviation Male 3103 0.3622 0.2779 Female 3267 0.3587 0.2697

Figure 36. Box plot of PVI distribution by gender.

As seen in Figure 36, the PVI distribution is similar between genders. There is some variation in gender by age, however, as Table 21 displays.

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Table 21. Mean PVI scores of males and females when broken down by age group. Gender Younger Middle Older Total Male 0.3679 0.3555 0.3632 0.3622 Female 0.3740 0.3571 0.3459 0.3587 Total 0.3710 0.3564 0.3548

While males are consistent across age groups, females differ with a range of

0.3459 (older) to 0.3740 (younger), values which represent the lowest and highest values in this table. Males and females in the Middle age range group have an almost equal mean PVI. In the younger group, females are slightly higher than males, and in the older group, males are slightly higher. Because of the slight difference in behavior depending on age group (i.e. females have a higher PVI when younger and a lower PVI when older),

Gender and Age were entered into the regression as an interaction but was not found to be significant. Considering the results of the regression analysis, the differences in PVI values between males and females in this sample are likely to represent chance variation, although the trend that younger females have the highest PVI values aligns with the finding that females with higher education exhibit higher PVI scores. That is, higher PVI scores (i.e. more stress-timed) may be the innovative pattern considering that younger females and those with more education produce more durational variability.

Other social variables considered in this study are Sector, Population (log), Years of Education, Years of Spanish Education, Age Learned English, Age Learned Spanish,

Spanish Language Use, and Wealth. Table 22 shows the mean PVI for variable group levels. In the case of several of the continuous variables, values are binned into discrete groups in the table to conceptualize patterns, but all were entered into the regression as continuous variables (including age). Furthermore, population is shown in this table as

179 the number indicative of the actual population in 2010 of locations where participants grew up, although in the actual regression analysis population is entered as log- transformed values.

Table 22. Mean PVI scores for additional social variables Variable N Mean PVI Sector 5 (Río Arriba region, 2,368 0.3534 inc. Santa Fe) 6 (middle Río Grande 2,153 0.3650 Valley, inc. Albuquerque) 9 (Northeast of Río 1,134 0.3804 Grande, inc. Mora) 10 (Mideast NM, inc. 715 0.3377 Torrence County and Santa Rosa) Years of Education 4-10 1,119 0.3520 11-15 2,938 0.3473 16-23 2,313 0.3619 Years of Spanish Education 0-4 5,345 0.3529 5-8 716 0.3719 10-16 309 0.3439 Age Learned English 0-4 1,729 0.3740 5-8 4,324 0.3612 10-20 317 0.4003 Age Learned Spanish 1 5,864 0.3603 2 106 0.3719 3 208 0.3352 4 98 0.3961 12 94 0.3688 Spanish Language Use 0-3 1,812 0.3489 4-6 3,757 0.3650 7-10 801 0.3407 Wealth 1 108 0.3347

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2 1,009 0.3637 3 2,711 0.3583 4 2,232 0.3662 5 310 0.3349 Population 23 - 870 2,802 0.3606 1,047 - 4,881 1,858 0.3591 8,329 - 13,753 700 0.3769 144,170 - 545,852 1,010 0.3507

Sector is the variable that codes the participants’ current residence and tests for regional variation, as each sector represents a different area of Central and Northern New Mexico, as displayed in Figure 7 in Chapter 4 (and replicated below in

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Figure 38). The results displayed in Table 22 above tell us that Sector 9 has a high PVI

(0.3804), especially in comparison to Sector 10 (0.3377), and when Sector is tested for differences in group means using an Approximative K-Sample Fisher-Pitman

Permutation Test, the result is significant (chi-squared = 13.164, p < .01). Conducting

Welch Two Sample t-tests for all possible combinations of sectors, we find that PVI scores for Sector 5 are significantly different from Sector 9 (t = -2.6854, p <.01), scores for Sector 6 are significantly different from Sector 10 (t = 2.3306 p < .05), and Sector 9 is significantly different from Sector 10 (t-value = 3.243, p < .01). Distributions of PVI scores by Sector are displayed in

Figure 37. The map of New Mexico delineated by Sectors is replicated below in Figure

38.

Figure 37. Box plot of PVI distributions by Sector

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Figure 38. Geographic sectors segmented by Bills and Vigil (2008:23).

The t-test results suggest that there is regional variation in PVI values across New

Mexico, and that Sector 9 has the highest PVI and Sector 10 has the lowest. Our hypothesis predicted that Sector 6 (which includes Albuquerque) would have the highest

PVI, due to its having a large population of English speakers and more urban centers.

Likewise, Northern New Mexico remained isolated for the longest period, maintaining tight-knit Spanish social networks (see, for example, Gonzales Velásquez’s 1992 ethnographic study of the women in Córdova, NM), and therefore we would expect the

183 lowest PVI scores there. However, influence from Mexican Spanish in the Central region of New Mexico (where Sector 6 crosses) might be a factor here. The PVI patterns we are seeing based on location may be influenced by the high population of Mexican Spanish speakers in certain areas of the state. This possibility will be explored further in Chapter

6. Again, it is important to keep in mind that this variable was not significant when considering the influence of other social factors on PVI values, and therefore the effect of

Sector is viewed as a trend only.

Table 22 also demonstrates that most speakers in the sample learned Spanish at home before going to school, between the ages of one and four. One speaker (Participant

152, Female, 29 years old) learned Spanish at the age of 12, and yet this speaker has a

PVI value (.369) that places her firmly in the average for this community, which indicates that having acquired English first does not necessarily correspond to having a more

English-like rhythm. This finding lends support to the general conclusion that the rhythm in this community does not appear to be strongly influenced by prolonged contact with

English. Furthermore, speakers who learned English latest, between the ages of ten and twenty, have the highest mean PVI scores (0.4003), not only of Age Learned English groups but of all the variables displayed in Table 22. The speakers who learned English the latest would be expected to have the lowest PVI scores. In sum, there is little evidence that the PVI of the Spanish speakers in this community is influenced by English.

Because there are so few speakers who learned Spanish after the age of one (i.e. one speaker each for two years old, four years old, and twelve years old, and two speakers that learned Spanish at the age of three), this variable was not included in the regression analysis. The PVI scores are shown in Table 22 to illustrate the differences in

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PVI scores across groups, although to be truly informative there would have to be more data points for speakers who learned Spanish after the age of one. In addition, Years of

Spanish Education was not added into the regression because the data points are also highly skewed towards lower values, and there would likely be a multicollinearity issue by adding this variable with age, because the majority of speakers who have many years of Spanish education are younger speakers. In fact, none of the speakers over 60 have more than seven years of Spanish education. Regarding Years of Education, there is less of an issue of multicollinearity because younger speakers range between 10 and 18 years of education, middle speakers range between 11 and 23 years of education, and older speakers range between 4 and 17 years of education. Furthermore, the mean PVI scores do not vary much per how many years of education the participant has attended. And, in fact, in Kendall’s rank correlation tau, the correlation is not significant (z=1.1471, tau =

0.01016, p = 0.1257).

Spanish Language Use is the self-reported variable that measures how much

Spanish (relative to English) the participant uses when interacting with friends and colleagues, with 0 being no Spanish and 10 being only Spanish. I would expect that speakers who use the least amount of Spanish, presumably indicating that they use mostly

English in their day-to-day lives, would have more English-like patterns in their prosody.

However, the mean PVI scores indicate that this is not the case; speakers who rate their

Spanish use between 0 and 3 have a mean PVI score of 0.3489, which is only slightly higher than speakers who interact in Spanish the most (mean PVI = 0.3407). Speakers in the middle, rating their Spanish use between 4 and 6, are right around the average for the entire population (0.3650). It is not the case, either, that younger speakers have lower

185 ratings and older speakers have higher ratings; there is variation across the board.

Younger speakers have values between 1 and 8, middle speakers have values between 0 and 9, and older speakers have values between 3 and 10.

The table includes two more variables, Wealth and Population, neither of which pattern in any discernible or meaningful way with PVI. For Wealth, the group with the lowest and highest Wealth scores have the lowest PVI (0.3347 for 1 and 0.3349 for 5), with slightly higher but similar PVI scores for scores between 2 and 4. Regarding population, there is again slight variation among groups. The group with the highest population represents speakers who grew up in the cities Albuquerque and Santa Fe.

While there is a high percentage of English speakers in these cities, many participants grew up in isolated areas of the cities that likely included tight-knit social networks (see, for example, Hudson-Edwards and Bills’ 1982 study on language shift and maintenance in Martineztown, Albuquerque). It is not the case that the speakers living in the most urban environments in New Mexico have the highest mean PVI scores. In fact, participants living in areas with population below 1,000 have an even higher average PVI than speakers in the highly urban areas, but this is not a significant difference.

5.2.3 Durational PVI Results Summary

When social variables were considered in a mixed-effects linear regression analysis to test how well they predicted PVI scores, one variable was found to have a significant effect: the interaction between Gender and Years of Education. The results of the interaction indicate that a more stress-timed pattern may hold overt prestige in this speech community. Whereas males vary little in PVI the more education they have, females exhibit an increase in PVI values with more education. These findings indicate that

186 women are sensitive to the prestige pattern of higher durational variability among successive vowels, resulting in a more stress-timed (English-like) rhythm. However, this possibility is speculative, as females have a lower PVI than males overall, though younger females have the highest PVI of age groups broken down by gender (see Table

20).

Like the variable pitch peak alignment, it was found that the Spanish syllable- timed rhythm has remained relatively stable across the three generations chosen in this sample to represent diachronic change throughout the twentieth century, and there are no strong indications of increasing influence from English. However, the range of speaker

PVI means, though situated within Spanish norms, overlap with the range of bilingual

English speaker means in Carter’s (2005) study. In other words, the range is wide for

Spanish and overlaps slightly with English. Even though age was not a significant predictor variable in the mixed-effects regression analysis, PVI scores increase inversely with age, indicating more stress-timed Spanish in younger speakers. However, this remains a trend and is not significant.

5.3 Pitch and Intensity PVI

The PVI formula, which measures relative variability in a particular dimension across successive segments, syllables, or feet, was also used in this study to measure variability in pitch and intensity across consecutive vowels. Pitch was chosen as a variable because

English is said to have a wider pitch range than Spanish (García Lecumberri 1995), or at least has a greater variation in range (Kelm 1995). Furthermore, intensity was considered because it is an aspect of prominence that lends relative importance to the perception of

187 syllable stress, along with pitch and duration. In other words, pitch and intensity are components of what makes syllables sound more prominent and affect the perception of a language’s rhythm (Arvaniti 2009, Kohler 2009). Both are considered in this study because if there is a change in one aspect of prominence, then this may affect other variables in their relative contribution to prominence in the language or dialect. For example, we may ask if pitch becomes more variable, does intensity become less so.

The use of the PVI measure to calculate mean variation in intensity and pitch has been applied previously in Low (1998) and Nokes and Hay (2012). In the current dissertation study, three different measures for pitch were calculated: (1) the difference in mean pitch across successive vowel segments, (2) the difference in maximum pitch across successive vowel segments, and (3) the difference in pitch at the midpoint of successive vowels. In addition, PVI scores were also measured for mean intensity across successive vowels. Final feet were excluded, as in the measurements for durational PVI.

Each measurement was included as a dependent variable in separate linear regression analyses. In all, 5,590 tokens were collected and analyzed for pitch and intensity variability (average 93.2 tokens per speaker; see Section 4.5.2 for an explanation of why there are fewer pitch PVI comparisons than durational PVI comparisons).

Like the PVI for durational variability, the higher the value, the more variable the parameter in consecutive vowels. A value of zero would represent no variability, a value of one absolute difference. There is less variability in pitch or intensity than in duration, so the scores on a whole are much lower than the PVI for durational variability. This does not indicate, however, that there is no variability in pitch or intensity; the results are still meaningful but are in a scale smaller than for duration. For example, the mean PVI for

188 maximum pitch for the speakers in this sample is 0.0693 (compare this to 0.36 durational mean PVI) with a mean PVI speaker range of .042 and .142. Recall that pitch was measured in the ERB-transformed scale. Table 23 displays the mean, median, and standard deviation of PVI for the different measurements in this study. Figure 39 displays the histogram of all tokens in the data for each dependent variable. Figure 40 displays box plots of the distributions for the dependent variables.

Table 23. Mean, median, maximum, and standard deviation of different PVI measurements for all speakers. Measurement Mean Median Maximum Std. Deviation Mean Pitch PVI 0.0669 0.0447 0.7439 0.0786 Maximum Pitch 0.06933 0.0461 0.7283 0.0821 PVI Midpoint Pitch 0.07035 0.0470 0.7366 0.0838 PVI Mean Intensity 0.04769 0.0388 0.3439 0.0391 PVI

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Figure 39. Histogram of PVI distribution of Mean Pitch (a), Maximum Pitch (b), Pitch at Vowel Midpoint (c), and Mean Intensity (d) for all tokens in the data.

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Figure 40. Box plot distributions of dependent variables.

Like the distributions for durational PVI, the distributions for pitch and intensity are right-skewed, and have a main cluster near the low end of the distribution. It is also worth pointing out that the distributions and values for Mean Pitch, Midpoint Pitch, and

Maximum Pitch are much the same and pattern similarly. Mean pitch is slightly less variable than the pitch at the midpoint of the vowel or than the maximum pitch. We will see that they are also conditioned in a similar manner by independent (social) variables.

The box plot graphs tell us that the interquartile range is narrow, with much scatter. This

191 seems to be the nature of the variable, pitch. Intensity is less variable than pitch in general, as is clear from the PVI values and the distributions displayed in Figure 39 and

Figure 40. It was also found that pitch nPVI significantly correlates with both mean intensity (Spearman’s rho = .0753, p < .0001) and intensity nPVI (Spearman’s rho =

.0830, p < .0001), though the effect is very weak. This means that as speakers increase vocal intensity, their f0 also rises, a result which finds support in the literature (Nokes &

Hay 2012:19-20, Buekers & Kingma 1997, Gramming et al. 1988).

The research question asked: if duration changes in its relative contribution to prosodic timing, do pitch and intensity change in parallel as a compensation strategy?

That is, as one acoustic cue to prominence (pitch, duration, or intensity) becomes more or less variable, do other acoustic parameters change in tandem? In a Spearman’s rank correlation test with speakers’ mean durational nPVI-V scores and speakers’ mean maximum pitch nPVI scores, no significant negative correlation was found (Spearman’s rho = -0.1249, p = .1709) (nor was a positive correlation found, Spearman’s rho = -

0.1249, p = .8291). That is, as durational PVI becomes more variable, pitch does not become less so. No significant negative correlation was found between mean durational nPVI-V scores and mean Intensity nPVI either (Spearman’s rho = 0.0607, p = 0.6776), nor was there a positive correlation (Spearman’s rho = 0.0607, p = 0.3224).

The following section presents the linear regression results which considered the same variables as for durational variability. Section 5.3.3 explores the distribution of PVI scores across various non-significant social variables.

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5.3.1 Linear Regression Results: Pitch PVI

Each pitch PVI measurement (Mean Pitch PVI, Maximum Pitch PVI, and Midpoint Pitch

PVI) was entered separately as a dependent variable into a mixed-effects linear regression analysis testing for significant predictors of variability, operationalized as the PVI-V.

Eight social variables (Gender, Age, Sector, Log Population, Years of Education, Age

Learned English, Spanish Language Use, Wealth), six interactions (Gender and Years of

Education, Gender and Wealth, Gender and Age Learned English, Age and Wealth,

Gender and Age, and Age and Spanish Language Use), and one random variable

(Speaker) were entered into the regression analyses using Rbrul (Johnson 2009) in the R statistical package (R Core Team 2016). Interactions were chosen based on observing patterns within cross-tabulations of data during exploratory analysis; there is one interaction added that was not tested in the durational PVI analysis: Age and Spanish

Language Use. The data set included 5,590 tokens of pitch PVI comparisons.

The regression analyses resulted in the same two significant effects on PVI scores for all three dependent pitch variables: Age (p < .05 for Mean Pitch PVI, p < .01 for

Maximum Pitch PVI, and p < .01 for Midpoint Pitch PVI) and Wealth (p < 0.01 for Mean

Pitch PVI, p < 0.01 for Maximum Pitch PVI, and p < 0.05 for Midpoint Pitch PVI). Table

24 presents the results from the linear regression in Rbrul for each dependent variable separately. The step-up and step-down models resulted in the same output.

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Table 24. Rbrul results for significant predictor variables on Pitch PVI. Multivariate Results: Mean Pitch PVI Variable Level Coefficient Age Continuous: +1 0 Wealth Continuous: +1 0.007 R2 total =0.049, Log likelihood = 6373.568, AIC = -12700.44, df = 5, Intercept= 0.029, Overall Mean = 0.067 Multivariate Results: Maximum Pitch PVI Variable Level Coefficient Age Continuous: +1 0 Wealth Continuous: +1 0.008 R2 total =0.041, Log likelihood = 6113.047, AIC = -12179.05, df = 5, Intercept= 0.027, Overall mean = 0.069 Multivariate Results: Midpoint Pitch PVI Variable Level Coefficient Age Continuous: +1 0 Wealth Continuous: +1 0.007 R2 total =0.047, Log likelihood = 6012.368, AIC = -11978.34, df = 5, Intercept= 0.031, Overall mean = 0.07

As the age of the speaker increases, the more likely they are to have a higher PVI score.

Put in other words, the younger the speaker, the more likely he or she is to have a lower

PVI score. This indicates that there is a correlation between age and pitch variability in that younger speakers exhibit less pitch variability on a local level within the phrase.

Recall that the primary research question asked whether there has been a change in intonation in New Mexican Spanish, possibly due to influence from English. Since

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English is thought to have a wider pitch range, or at least a more variable one, I hypothesize that as age decreases, or as birth year increases, the PVI scores for pitch would increase. Table 25 provides the raw PVI scores for speakers in this study broken down into age groups (keep in mind that age is entered as a continuous variable in the regression analyses), in addition to the number of comparisons for each group. Figure 41 displays box plots with the IQR distributions for the three age groups for the three dependent pitch variables.

Table 25. Mean PVI pitch variables broken down by age group. Age Group Mean Max Pitch Midpoint N Pitch PVI PVI Pitch PVI Younger 0.0573 0.0583 0.0599 1771 Middle 0.0721 0.0756 0.0766 1875 Older 0.0706 0.0733 0.0738 1944

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Figure 41. Box plots of PVI distributions by age group for Mean Pitch PVI, Maximum Pitch PVI, and Pitch at the Vowel Midpoint PVI.

A consideration of the PVI values regarding pitch show an interesting pattern: while middle and older speakers are fairly similar, the younger speakers have a lower

PVI score across the three pitch PVI variables, and the box plots demonstrate that the younger speakers exhibit a narrower Inter-Quartile Range. The difference in group means is significant for all three pitch variables; the results of the Approximative K-Sample

Fisher-Pitman Permutation Tests are displayed in Table 26.

Table 26. K-Sample Fisher-Pitman Permutation Tests showing significant difference across age group means. Chi-squared P-value Mean Pitch PVI 38.636 *** < 0.0001 Maximum Pitch PVI 47.153 *** < 0.0001 Midpoint Pitch PVI 41.177 *** < 0.0001

To determine which group means are significantly different, a Wilcoxon rank sum test (a non-parametric U-test) was conducted for each level comparison for the three

Pitch PVI variables. For each variable, the group Younger is significantly different from

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Middle and Older. In addition, Middle and Older are significantly different from each other for mean and midpoint pitch (with a much smaller p-value), but not for maximum pitch. The results are displayed in Table 27.

Table 27. Multiple Comparisons table for Wilcoxon rank sum tests for Age Group levels. Mean Pitch PVI Age GroupAge (x) Group Mean(y) Mean W- p-value 95% Confidence Interval PVI (x) PVI (y) value Lower BoundUpper Bound Younger Middle 0.0573 0.0721 1476600 ***<.001 -0.0094 -0.0045 Older 0.0573 0.0706 1440700 ***<.001 -0.0134 -0.0083 Middle Older 0.0721 0.0706 1737300 * < 0.05 -0.0060 -0.0007 Maximum Pitch PVI Younger Middle 0.0583 0.0756 1463300 ***<.001 -0.0107 -0.0053 Older 0.0583 0.0733 1491400 ***<.001 -0.0119 -0.0064 Middle Older 0.0756 0.0733 1798100 0.4734 -0.0037 0.0017 Midpoint Pitch PVI Younger Middle 0.0599 0.0766 1468300 ***<.001 -0.0102 -0.0051 Older 0.0599 0.0734 1433300 ***<.001 -0.0143 -0.0089 Middle Older 0.0766 0.0734 1739200 * p < 0.05 -0.0062 0.0007 ***The mean difference is significant at the .001 level. * The mean difference is significant at the .05 level.

In Spearman's rank correlation rho tests, there is a highly significant positive correlation (p < .0001) between age and PVI for all three pitch PVI variables. That is, the greater the age, the higher the PVI value, which the regression results also tell us. In other words, speakers are more likely to have lower PVI values the younger they are. While I

197 find a difference in younger speakers in comparison to both middle and older speakers, the difference is not in the expected direction. In other words, I expected more pitch variability in younger speakers but they are exhibiting the least amount across successive vowel segments. Possible reasons why this is so will be discussed in the following chapter.

Wealth is also found to significantly predict pitch PVI, with a positive correlation.

In other words, the greater the wealth, the higher the pitch PVI scores. Table 28 displays the PVI scores by Wealth and Figure 42 features scatter plots for the PVI variables by

Wealth.

Table 28. Mean PVI scores by wealth; the higher the value, the higher the wealth of the participant. Wealth Mean Pitch Maximum Midpoint Total N PVI Pitch PVI Pitch PVI 1 0.0674 0.0786 0.0734 101 2 0.0574 0.0587 0.0599 910 3 0.0643 0.0665 0.0677 2,380 4 0.0739 0.0758 0.0778 1,904 5 0.0718 0.0794 0.0744 300

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Figure 42. Scatter plots of PVI distributions by Wealth.

The slopes in the scatter plot regression lines are positive, suggesting that the greater the wealth, the higher the variability in pitch. Although studies have found greater variability in pitch for English than Spanish (Kelm 1995), this particular method for testing pitch variability (i.e. pitch PVI) has rarely been used for English. Nokes and Hay (2012) used the PVI method on New Zealand English, but it is not clear what measurement for pitch was used, nor were group scores provided (neither for pitch nor intensity). Therefore, I am making as assumption that English would have greater pitch PVI means than Spanish

(and from the graph of New Zealand English speakers provided in Nokes & Hay

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2012:19, it appears that the average is between .15 and .20, which does indicate more variability than the Spanish of the speakers in the current study). However, to make the findings in the current study truly comparable, the same method (i.e. PVI measurement) would have to be applied to English of the same region, and ideally of the same speakers.

In sum, the factors that seem to play the biggest roles in pitch variability in this community are age and wealth. The effect for age is not in the expected direction; the results show that the younger the speaker, the lower the PVI values. In other words, speakers exhibit less pitch variability the younger they are. The other significant main effect on pitch PVI values is wealth, which is in the expected direction; the wealthier the speaker, the more likely he or she is to exhibit greater pitch variability. The following section will describe the regression results for intensity. The non-significant social variables for both pitch and intensity PVI will be considered together in more depth in the following section. Variables which were not entered into the regressions but are still informative when understanding the language situation in New Mexico will also be discussed.

5.3.2 Linear Regression Results: Intensity PVI

The intensity PVI variable measured the mean intensity of consecutive vowels across phrases, excluding the final foot. The vowels measured for pitch PVI measurements were the same vowels included in the intensity PVI measurement. A script was used to extract measurements for all four dependent variables at once for optimizing consistency. Mean

Intensity PVI was entered as a dependent variable into a mixed-effects regression analysis testing for significant predictors of variability in the PVI score. This analysis

200 included the exact same set of external independent variables as the pitch PVI regressions except that interactions were not included after exploratory data analysis. The mixed- effects regression analysis was run in the R statistical package (R Core Team 2016) using

Rbrul (Johnson 2009). The data set included 5,590 tokens of intensity PVI comparisons, with a mean Intensity PVI of 0.0477 for the entire data set.

The regression analysis showed one significant effect on mean intensity PVI:

Spanish Language Use (p < .01). Table 29 presents the results from the mixed- effects linear regression in Rbrul.

Table 29. Rbrul results for the significant predictor variable on mean intensity PVI. Multivariate Results: Mean Intensity PVI Variable Level Coefficient Spanish Language Use Continuous: +1 0.002 R2 total =0.039, Log likelihood = 10254.36, AIC = -20475.64, df = 4, Intercept= 0.04, Overall Mean = 0.048

The variable Spanish Language Use gets at daily Spanish use and therefore exposure to and perhaps dominance of Spanish. The results show that as Spanish

Language Use increases, so does the likelihood that the speaker has a higher intensity

PVI score. In other words, the more a speaker uses Spanish in their day-to-day interactions, the more likely they are to exhibit intensity variability across successive vowels. The binned distribution for Spanish Language Use is displayed in Table 30 below. Figure 43 presents a scatter plot for mean Intensity PVI by Spanish Language

Use.

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Table 30. Mean PVI scores for Spanish Language Use. Variable Mean Total N Intensity PVI Spanish Language Use 0-3 0.0446 1,628 4-6 0.0477 3,272 7-10 0.0549 690

Figure 43. Scatter plot of mean Intensity PVI distributions by Spanish Language Use with regression lines.

In sum, the positive correlation signifies that the more Spanish used daily, the greater the mean intensity PVI. It is not clear why higher variability in intensity correlates with

Spanish Language Use, although it is possible that highly proficient and confident speakers make use of loudness to a greater extent as a cue to prominence than less proficient speakers.

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5.3.3 Pitch and Intensity PVI: Non-significant Social Variables

Other social variables considered in this study are Gender, Sector, Population (log- transformed), Years of Education, Years of Spanish Education, Age Learned English,

Age Learned Spanish, and Spanish Language Use. Because of multicollinearity, Years of

Spanish Education and Age Learned Spanish were excluded from the linear regression.

However, all variables and their distributions are shown here in Table 31. Several of the continuous variables such as age are binned into discrete groups in the table to make it easier to see patterns, although all were entered into the regression as continuous variables to avoid the arbitrariness involved with determining how groups are binned.

Like the section on durational PVI, population is shown here as the actual population in

2010, but in the regression analysis population was entered as log-transformed values.

Table 31. Mean PVI scores for additional social variables Variable Mean Pitch Maximum Midpoint Mean Total N PVI Pitch PVI Pitch PVI Intensity PVI Age Group Younger 0.0573 0.0583 0.0599 0.0470 1771 Middle 0.0721 0.0756 0.0766 0.0479 1875 Older 0.0706 0.0733 0.0738 0.0480 1944 Gender Female 0.0680 0.0713 0.0716 0.0485 2,894 Male 0.0657 0.0672 0.0690 0.0469 2,696 Sector 5 (Río Arriba 0.0676 0.0718 0.0703 0.0477 2,091 region, inc. Santa Fe) 6 (middle 0.0683 0.0705 0.0721 0.0471 1,871 Río Grande Valley, inc. Albuquerque) 9 (Northeast 0.0656 0.0642 0.0697 0.0476 987 of Río Grande, inc.

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Mora) 10 (Mideast 0.0628 0.0657 0.0664 0.0497 641 NM, inc. Torrence County and Santa Rosa) Years of Education 4-10 0.0617 0.0669 0.0645 0.0495 1,013 11-15 0.0687 0.0704 0.0728 0.0493 2,506 16-23 0.0672 0.0692 0.0702 0.0449 2,071 Years of Spanish Education 0-4 0.0671 0.0691 0.0707 0.0480 4,652 5-8 0.0606 0.0649 0.0632 0.0470 669 10-16 0.0787 0.0835 0.0813 0.0439 269 Age Learned English 0-4 0.0612 0.0625 0.0641 0.0483 1,560 5-8 0.0685 0.0714 0.0722 0.0477 3,759 10-20 0.0776 0.0799 0.0807 0.0435 271 Age Learned Spanish 1 0.0669 0.0697 0.0704 0.0479 5,149 2 0.0672 0.0662 0.0707 0.0470 94 3 0.0510 0.0532 0.0517 0.0435 177 4 0.1002 0.0917 0.0989 0.0525 78 12 0.0684 0.0637 0.0762 0.0392 92 Spanish Language Use 0-3 0.0624 0.0654 0.0649 0.0446 1,628 4-6 0.0689 0.0710 0.0731 0.0477 3,272 7-10 0.0678 0.0705 0.0700 0.0549 690 Wealth 1 0.0674 0.0786 0.0734 0.0525 101 2 0.0574 0.0587 0.0599 0.0480 910 3 0.0643 0.0665 0.0677 0.0486 2,380 4 0.0739 0.0758 0.0778 0.0467 1,904 5 0.0718 0.0794 0.0744 0.0443 300 Population 23 - 870 0.0664 0.0686 0.0690 0.0463 2,456 1,047 - 4,881 0.0735 0.0739 0.0779 0.0501 1,631 8,329 - 0.0508 0.0557 0.0552 0.0482 584

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13,753 144,170 - 0.0669 0.0717 0.0701 0.0468 919 545,852

The primary research question asked whether there has been a change in intonation in

New Mexican Spanish due to influence from English. Age was found to correlate positively with pitch PVI in that the greater the age, the higher the pitch PVI values

(indicating more variability in pitch across successive vowels). Regarding intensity, I hypothesized that as duration and pitch (two acoustic correlates of intonation) become more or less important for signaling prominence, intensity would change to compensate.

Since I found out that pitch becomes less variable for younger speakers, intensity may become more variable for them. However, even though pitch variability is lower among younger speakers, variability in intensity is not higher for them. It is clear that not only is there less variability in mean intensity PVI overall than for pitch, but that the variability is consistent across age groups. The group differences are not significant (chi-squared =

0.74794, p = 0.6906, Approximative K-Sample Fisher-Pitman Permutation Test).

Considering age as a continuous variable, the correlation between age and PVI scores is not significant (rho = -0.0028, p = 0.4181, Spearman’s rank correlation rho). In fact, as the box plot in Figure 44 demonstrates, distributions of mean Intensity PVI values are very similar for all three age groups.

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Figure 44. Box plot of PVI distributions by age group for mean Intensity PVI.

Regarding Gender, in all four PVI measurements, females exhibit slightly more variability than males. While not significant when other variables are controlled for in the regression, the differences in group means are significant in a Wilcoxon rank sum test for mean pitch PVI (W=4100400, p < .001) and for midpoint pitch PVI (W=4108000, p <

.001), but not for maximum pitch PVI (W=3949600, p = 0.4214) nor mean intensity PVI

(W=3815000, p = 0.1534).

Although not significant, the trend for Years of Education, a variable associated with socioeconomic status, and pitch PVI appears to be that the more years of education a speaker has, the more variability in pitch there is. This trend is along the same line as

Wealth, which was found to significantly correlate with pitch PVI. When other variables are not controlled for, Years of Education is found to significantly correlate with mean

206 intensity PVI (z = -3.4516, tau = -0.0326, p < 0.001). That is, the more years of education a speaker has, the lower the variability in intensity across successive vowels. This negative correlation can be seen in the scatter plot in Figure 45.

Figure 45. Scatter plots for Years of Education and Age Learned English by mean intensity PVI.

In addition to Years of Education, Age Learned English is also found to significantly correlate with variability in intensity PVI when the variable is considered individually (z = -2.61, tau = -0.0256, p < 0.01). The scatter plot for Age Learned English by mean intensity PVI is also displayed in Figure 45, which demonstrates a negative correlation between the age English was acquired and intensity PVI. It seems contradictory that the later a speaker acquired English, the lower their PVI intensity is, yet the more Spanish they use on a day-to-day basis (i.e. Spanish Language Use), the more intensity variability they exhibit. However, this is likely an artifact of one or two speakers, because when all variables are controlled for in the mixed-effects regression analysis and Speaker is entered as a random variable, the effect of Years of Education is

207 no longer significant. The only variable that remains a significant predictor of mean

Intensity PVI is Spanish Language Use.

We also see a trend in Age Learned English for pitch PVI, although in this case the correlation is positive (see Figure 46). There are only three speakers who learned

English between the ages of 10 and 20. One of these speakers is Participant 70 (Age 58,

Female), who has a mean pitch PVI of 0.0982 and learned English at age 10. Another speaker is Participant 144, who learned English at age 11 and has a mean pitch PVI of

0.0904 (Age 83, Male). The third participant in this group (Participant 214, age 76, Male) is the participant who learned English the latest, at age 20, and this speaker has a low mean pitch PVI (0.0454). It is difficult to say whether physiological change due to age plays a role here, but this is a factor to be considered. However, Participant 144 is even older than Participant 214 and has a high PVI score, higher than the total average. The details of these three speakers are shown in Table 32.

Figure 46. Scatter plot for Age Learned English by mean pitch PVI,

Table 32. Socio-demographic information and raw PVI scores for participants who

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learned English at age 10 or later. Participant Age Age at Gender Mean Maximum Midpoint Learned time of Pitch PVI Pitch PVI Pitch PVI English interview 70 10 58 F 0.0982 0.1074 0.1043 144 11 83 M 0.0904 0.0892 0.0939 214 20 76 M 0.0454 0.0459 0.0453

Years of Spanish Education also provides an interesting trend. The pitch PVI values are highest for those with the most years of Spanish education. However, any discernible pattern is complicated by the fact that speakers who have had between zero and four years of Spanish education have higher pitch PVI means than speakers who have had between five and eight years. This variable was not included in the regression because the majority of speakers have between zero and four years of education (n=51) and this variable has a high level of multicollinearity with years of education (i.e. the three speakers who have had between 10 and 16 years of Spanish education also had a high number of years of regular education, between 16 and 17 years).

Spanish Language Use, the variable that gets at daily Spanish use with friends and colleagues and therefore reflects exposure to and use of Spanish on a daily basis, was found to have a significant effect on mean Intensity PVI. For pitch, the variable was not significant when controlling for other independent variables and adding Speaker as a random variable into the mixed-effects regression analysis. Unlike intensity, which was shown to consistently increase in variability with more Spanish use, the pitch PVI is highest for those with mid-level Spanish use (a rating between 4 and 6), although speakers with a rating of 4-6 and 7-10 pattern similarly. However, speakers who report very little use of Spanish with friends and co-workers (rating of 0-3) have the lowest PVI

209 means, conveying less pitch variability. This trend aligns with my finding of age in that the younger the speaker, the lower the pitch PVI, which perhaps has to do with a lack of dominance or proficiency in Spanish. Furthermore, it is the same direction of effect with mean Intensity PVI in that infrequent daily Spanish use correlates with low variability.

Let’s now consider Population. There is no clear-cut pattern; speakers who live in the lowest populated towns (under 1,000) have approximately the same pitch and intensity PVI scores as those living in the highest populated towns. The highest PVI belongs to the second grouping of population, those living in populations between 1,047 and 4,881. However, the PVI then takes a dip for speakers living in towns with populations between 8,329 and 13,753, before rising again for the highly-populated locales. In other words, population does not appear to meaningfully pattern with PVI.

Sector also has no discernible patterns for pitch nor intensity PVI. Pitch and intensity variability across successive vowels does not seem to exhibit noticeable differences across regions.

Wealth patterns differently for intensity PVI than for pitch. For pitch, the slope is positive in the scatter plot regression lines, suggesting that the greater the wealth, the higher the variability in pitch. With intensity, on the other hand, it appears that the higher the speaker’s wealth, the lower the intensity PVI. It is unclear why this is so. However, the findings for Wealth and Intensity pattern with the finding for Years of Education, another variable associated with socioeconomic status, which also exhibited a negative correlation with mean intensity PVI. In other words, the more wealth and the more years of education, the lower the variability in intensity across successive vowels. This negative correlation can be seen in the scatter plot in Figure 47.

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Figure 47. Scatter plot of mean Intensity PVI by Wealth.

For pitch, the greater the wealth, the more variability in pitch is likely across consecutive vowels, a significant effect. Meanwhile, the trend for intensity, although non-significant, is in the opposite direction: the higher the wealth, the less likely speakers are to exhibit variability in intensity across successive vowels. We may speculate that as pitch becomes more variable (and therefore more important for signaling prominence), then intensity becomes less so.

5.3.4 Pitch and Intensity PVI Results Summary

Pitch PVI is significantly conditioned by Age and Wealth. The effect for age is not in the expected direction, however; the mixed-effects regression shows that the older the speaker, the more pitch variability is likely in his or her speech. Put another way, speakers are more likely to have lower PVI values the younger they are. The effect for wealth is in the same direction; the higher the wealth of the speaker, the higher the pitch

PVI values. In other words, speakers who are wealthier are also more likely to exhibit

211 more pitch variability. For pitch PVI, then, older speakers and those who are wealthier exhibit more pitch variability.

The mixed-effects regression for intensity showed one significant conditioning variable on intensity PVI: Spanish Language Use. The more a speaker uses Spanish with friends and colleagues on a daily basis, the higher their intensity PVI, which may be a result of higher proficiency leading to an increased use of intensity as a cue to prominence. Similarly, for pitch PVI, speakers who report very little use of Spanish with friends and co-workers (ratings of 0-3) have the least amount of pitch variability. This trend aligns with my finding of age in that the younger the speaker, the lower the pitch

PVI, which perhaps has to do with a lack of dominance or proficiency in Spanish. How the overall findings answer the research questions regarding intonation and prosody will be discussed and explored in the following chapter.

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Chapter Six: Discussion and Conclusion

6.1 Introduction

This study focused on three prosodic features which are known to differ in quantitative terms between Spanish and English: peak alignment, pitch variability, and rhythmic timing. This section will go through the research questions one at a time in order to elucidate whether there is evidence for prosodic change in terms of peak alignment, pitch variability, and rhythmic timing, and whether there is any evidence of social conditioning on the variable features. This chapter revisits effects presented in the Results chapter and summarizes and interprets them, relating the findings to the original research questions.

This chapter also discusses why NMS has been resistant to influence from English, a finding also corroborated in other studies of NMS grammar and phonology. Finally, this chapter considers a prosodic feature which was not quantitatively measured in this study but which may be a distinct feature of NMS, and therefore sets the stage for future research on NMS prosody.

Results of the phonetic analyses in the NMCOSS sample indicate that there is no evidence for change in apparent-time, demonstrating that the features considered in this study have not significantly changed in a more English-like direction throughout the 20th century, even though this period has been marked by a societal increase in bilingualism with a concurrent loss of Spanish language use. The results demonstrate that the prosodic patterns analyzed in this study are similar to patterns in Spanish monolingual varieties, in particular those spoken in Peninsular Spain and central Mexico on which the principal descriptions of broad focus declarative pre-nuclear pitch accents are based (e.g. Beckman et al. 2002, de-la-Mota et al. 2010; Estebas-Vilaplana & Prieto 2010, Prieto et al. 1995,

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Face 2003). That is, the prosodic patterns in NMS considered in this study are well within the typical range of variation for monolingual varieties of Spanish.

6.2 Research Questions

The research questions and their hypotheses introduced in Chapter 1 are repeated here:

1. Has Spanish remained stable in New Mexico over the twentieth century in terms of prosody, or have prosodic patterns in NMS been influenced by prolonged contact with English in the form of Spanish-English bilingualism? In particular,

(a) How do patterns in NMS compare to patterns in monolingual varieties of

Spanish, in particular Peninsular (Face 1999, Face & Prieto 2007, Prieto et al. 1995,

Estebas-Vilaplana & Prieto 2010, among others) and contemporary Mexican Spanish (de- la-Mota et al. 2010)?

(b) How do patterns in older speakers compare to patterns in younger speakers, with age measured as a continuous variable?

(operationalized as variability across successive vowel segments), do pitch and intensity change in parallel as a compensation strategy? That is, as one acoustic cue to prominence

(pitch, duration, or intensity) becomes more or less variable, do other acoustic parameters change in tandem?

(d) Is there a prosodic hierarchy in terms of the susceptibility of different prosodic variables to change? That is, are some prosodic features more likely to change than others?

I hypothesized that peak alignment patterns in NMS have been influenced by

214 prolonged contact with English. In particular, pre-nuclear broad focus declarative pitch accented syllables were expected to exhibit f0 peak alignment within the tonic syllable, similar to English (e.g. Silverman & Pierrehumbert 1900) and contact varieties of

Spanish (e.g. O’Rourke 2005, Colantoni & Gurlekian 2004, Michnowicz & Barnes 2013,

Barnes & Michnowicz 2013), whereas central Mexican Spanish and non-contact varieties of Spanish exhibit delayed peak alignment (Prieto & Roseano 2010, de-la-Mota et al.

2010). In addition, I hypothesized that peak alignment would be more similar to monolingual varieties of Spanish the older the speaker.

Regarding rhythm, I hypothesized that rhythmic timing in NMS has been influenced by prolonged contact with English. I hypothesized that NMS has become more stress-timed throughout the twentieth century. Regarding pitch, I hypothesized that pitch variability, a local measure of pitch range, was expected to increase the younger the speaker, since English exhibits a wider pitch range than Spanish (Kelm 1995, Enzinna

2015, Navarro Tomás 1944, Stockwell & Bowen 1965, Cruttenden 1986). Furthermore, as durational variability increases or decreases, pitch and intensity were expected to change inversely (Nokes & Hay 2012).

The second part of the research question is interested in the social drivers of prosodic change. This asks which socio-demographic and language use factors correlate with English-influenced Spanish intonational and prosodic patterns, if change is found.

I hypothesized that sociodemographic, language background and usage factors would correlate with whether NMS speakers exhibit English-influenced Spanish intonational and prosodic patterns.

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6.2.1 Peak Alignment Discussion

Whereas the original hypothesis of this study predicted that pitch alignment scores would decrease as birth year increased, indicating a change in apparent-time toward earlier alignment due to influence from English, these data clearly do not support that. In fact, the age group with the earliest alignment are the oldest speakers, although the means are not significantly different from the younger speakers. It is unclear why the middle speakers (aged 40-60) would have the latest alignment. One possibility is that the Spanish of this age group has experienced more influence from Mexican Spanish, rather than

English. One thing is clear, however: all three groups exhibit post-tonic alignment, and are exhibiting clear monolingual Spanish patterns, although the variation and distributions across speakers is considerable. There is no reason to think that the pitch accent for pre-nuclear broad focus declaratives in NMS is anything other than L+>H*, the pitch accent described for this context in multiple monolingual varieties of Spanish

(Prieto & Roseano 2010).

The pattern of delayed alignment could be reinforced by the presence of Mexican

Spanish, which has had a strong presence in the state via immigration throughout the twentieth century. There is evidence that Mexican Spanish represents the prestige variety, and formal registers for NMS speakers are reserved either for Mexican Spanish or

English. For example, Kravitz (1985) notes that for Martineztown residents in

Albuquerque, a historically traditional New Mexican barrio, models of formal Spanish are generally in standard Mexican Spanish and are available to residents in the form of church sermons, radio, Spanish language programming, and newspapers (e.g. El

Hispano).

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Although no social variables proved significant in the peak alignment analysis, the trends of Gender and Population are informative regarding the social status of alignment in this speech community. The difference in mean alignment score by gender is slight, and does not interact with other variables. We would expect that if a change were occurring in the community, it would be led by females (Labov 1990). Since both genders display similar patterns, with females displaying even later alignment than males

(and recall the footnote that explains how Gender becomes significant when outliers are excluded, with males displaying earlier alignment than females), it does not seem likely that there is a change toward earlier alignment; if anything, the pattern is likely reinforced by Standard Mexican Spanish, with post-tonic peak alignment in pre-nuclear broad focus declaratives (de-la-Mota et al. 2010). The correlation between alignment score and population is not significant in the regression analysis, and furthermore, the correlation is not in the expected direction, based on the hypothesis. The trend displayed in these data is that the greater the population, the higher the alignment score. It is possible that the higher alignment scores in urban environments may be due to more exposure to Mexican

Spanish in highly populated areas. Again, this possibility of a change, not towards

English-like patterns but towards Mexican Spanish-like patterns, may be a likely explanation for alignment patterns in pre-nuclear pitch accents of broad focus declaratives in New Mexican Spanish.

The variables found to significantly condition earlier alignment are internal linguistic variables that have been found to condition alignment in numerous studies of monolingual Spanish varieties (e.g. Prieto et al. 1995, Face 2002, Prieto & Torreira 2007,

Llisterri et al. 1995, among others). These variables are: Tonic Syllable Type, Intervening

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Unstressed Syllables, Voiceless Segment in Tonic Syllable, and Voiceless Segment in

Post-Tonic Syllable. Curiously, Barnes and Michnowicz (2013) find differences in how the linguistic variables in their study condition alignment, specifically with the variables

Intervening Unstressed Syllables and Syllable Type. Their study looks at Chipilo

Spanish, a variety spoken in Mexico that is in contact with Veneto. They find early peak alignment to be the norm, a finding they expected based on early alignment patterns found in multiple contact varieties of Spanish. Barnes and Michnowicz (2013:117) suggest that Intervening Unstressed Syllables is not significant in their data because early peak alignment in this variety “does not appear to be solely the effect of phonetic factors conditioned by the task, and instead may represent true intonational differences in

Chipilo Spanish.” They argue that Alvord (2010) (and other such studies) find phonetic effects such as intervening unstressed syllables conditioning peak alignment because in these varieties early peak alignment (in broad focus contexts) is not an intonational norm, or in other words is not characteristic of the variety. Alvord’s (2010) study of Miami

Cuban Spanish compares peak alignment across three immigration groups based on how recently the participant or his/her parents came to the United States from Cuba. In all three groups, Alvord (2010:18-20) finds no significant differences in alignment, which leads him to conclude that late (post-tonic) alignment is the community norm. It may be the case that the speech community in this dissertation study patterns like that in Alvord

(2010) and unlike in Barnes and Michnowicz (2013) because early peak alignment is not characteristic of the pre-nuclear broad focus declarative pitch accent (and therefore is not phonologically specified), but rather is conditioned solely by phonetic factors. This also explains why Barnes and Michnowicz (2013) find an effect for syllable type in the

218 opposite direction than this study and other studies on monolingual Spanish (e.g. Prieto &

Torreira 2007). In other words, alignment is conditioned by different factors in Chipilo

Spanish because it functions differently than varieties in which early alignment is not part of the phonological pitch accent make-up for this context.

6.2.2 Rhythmic Timing Discussion

Findings suggest that rhythmic timing in New Mexican Spanish has remained relatively stable across the three generations chosen in this sample to represent apparent time in the twentieth century, and there are no clear indications of influence from English. The social variable that was found to have a significant effect on PVI scores is the interaction between Gender and Years of Education, suggesting that a more stress-timed pattern may hold overt prestige in this community. Whereas males vary little in PVI the more education they have, females exhibit an increase in PVI values with more education.

Even though Wealth is not significant, the trend for Wealth, another socioeconomic variable, patterns in the same way as Years of Education. Taken together, these results could be evidence that a higher PVI value has prestige in this community, as women are sensitive to the prestige variant. If higher socioeconomic status is associated with a particular variant, this is evidence that the variant has social value (Labov 1990). For men, on the other hand, there may be covert prestige associated with use of the nonstandard variant, in this case, a more Spanish-like rhythm pattern.

Even though the distribution of speaker mean PVIs overlaps with Carter’s (2005)

Hispanic English speakers, the scores are still well within the range of variation for monolingual Spanish varieties. PVI scores do increase inversely with age, though Age

219 was not a significant variable in the regression analysis, so this trend must be taken cautiously. Furthermore, there is evidence that Mexican Spanish has reinforced the syllable-timing pattern in New Mexican Spanish, like peak alignment. For example, regarding the variable Sector, the sector that was expected to have the highest PVI scores due to more English speakers and more urban environments (i.e. Sector 6, which contains

Albuquerque and Bernalillo County) was higher than average. It may be that this is in part influenced by the higher population of Mexican Spanish speakers in these urban areas. Population patterns similarly; the less populated areas have high PVIs and places like Albuquerque have low PVIs, which again suggests syllable-timed rhythmic timing is maintained in urban centers because of Mexican Spanish influence. In sum, it is not the case that the speakers living in the most urban environments in New Mexico have the highest mean PVI scores. As stated in the Results section, participants living in areas with a population below 1,000 have an even higher average PVI than speakers in the highly urban areas. It should be kept in mind that not all small towns in Northern New Mexico maintained Spanish at the same rate or had the same demographic ratios of Hispanos to

Anglos (see Ortiz 1975 for a comparison of English arrival into Arroyo Seco and nearby

Taos, for example).

6.2.3 Pitch PVI Discussion

Pitch PVI was found to be significantly conditioned by Age and Wealth. Specifically, as the age of the speaker increases, the more likely they are to have a higher pitch PVI score. In other words, younger speakers exhibit less pitch variability on a local level within the phrase. This pattern was not in the expected direction; the hypothesis stated

220 that if English were influencing NMS prosody, then a wider pitch range with younger speakers would be expected. What explains a decrease in pitch variability as speakers’ birth years increase? It is possible that younger speakers exhibit less variability due to lower proficiency in Spanish, in the same way that L2 speakers have been shown to exhibit deviations from L1 pitch range (Backman 1979, Mennen, Schaeffler, & Dickie

2014). In addition, English and Spanish speakers have been shown to exhibit differences in pitch range in their L2, regardless of L1 pitch range patterns. For example, Kelm

(1995), found that English speakers produced a narrower pitch range when speaking their

L2, Spanish, than when speaking their L1, English. The same occurred for the L1 Spanish speakers when speaking English. In other words, younger speakers in the NMCOSS may be exhibiting a decrease in pitch variability because they lack dominance or proficiency in Spanish. Although proficiency was not included as a variable in this study, the lack of

Spanish dominance in the younger speakers (and many middle-aged speakers) is evident from their interviews, which are characterized by frequent pauses and hesitations and difficulty in sustaining conversation in Spanish. For example, in the interview for a 27- year-old male from Cleveland (Interview 221), the interviewer switches to English halfway through and does not attempt to facilitate any more conversation in Spanish because the speaker is clearly not comfortable with maintaining speech in Spanish. A reduction in pitch range (i.e. less variability locally) may be a type of simplification, such that speakers with a reduction in exposure to and use of Spanish may not have the full range of options available to more dominant speakers (see, for example, the discussion of the subjunctive mood in Silva-Corvalán 1994). The decrease in pitch range may also be an effect of linguistic insecurity, if speakers are not confident in their Spanish. Of course,

221 these results contradict the hypothesis of interference, which predicts that if English is the

L1, then interference in the L2, Spanish, would result in increased pitch range. It is hard to say why this does not occur. It may be that pitch range has a different outcome in such situations than expected; it would be interesting to analyze the outcome of pitch range in different language contact settings.

Regarding Wealth, it was found that the higher the wealth of the speaker, the more pitch variability they are likely to exhibit. This effect is independent of age; in other words, there is stable stratification with this variable, supported furthermore by the fact that there is no interaction between wealth and age in the analysis. Higher socioeconomic status is associated with the use of English as a home language for Hispanics (Lopez

1978), yet this does not necessarily mean they have diminished dominance in Spanish; on the contrary, Bills and Vigil (2008:272-273) note that speakers with higher socioeconomic status tend to also have more exposure to Standard Spanish due to international travel and connections and more formal Spanish study. In other words, unlike younger speakers who are exhibiting a lack of pitch variability that may be due to diminished proficiency in Spanish, speakers with more wealth may have high proficiency in Spanish and in English, which may influence their increase in pitch variability.

Although not significant, the trend for Years of Education and pitch PVI is similar to Wealth in that the more years of education a speaker has, the more variability in pitch there is. This trend patterns in the same direction as Wealth, and education is another dimension of socioeconomic status, with more years of education correlating with higher socioeconomic status. As suggested for wealth, if a speaker has more years of education, it is likely that they also have had more exposure to English. Therefore, more pitch

222 variability with more years of education could be an indirect influence from English, since the language of instruction for most participants in NMCOSS has been English

(Bills & Vigil 2008:272). Bills and Vigil (2008:46, 272-273) also note that participants in the NMCOSS who have had more years of education (which itself is intercorrelated with

Years of Spanish Education) tend to have more familiarity with Standard Spanish, and for this reason tend to avoid nonstandard (Traditional New Mexican) Spanish forms such as vide for vi ‘I saw’. This connection between familiarity of Standard Spanish and more years of education is independent of any formal Spanish study, and is likely due to network connections and international travel.

A word of caution is necessary here. Although prior studies have found greater variability in pitch for English than Spanish (e.g. Kelm 1995), this particular method for testing pitch variability (i.e. pitch PVI) has rarely been used for English. Nokes and Hay

(2012) used the PVI method on New Zealand English, but it is not clear what measurement for pitch was used (e.g. Hertz, ERB log-transformed values, as in this study, or Semitones), nor were group scores provided (neither for pitch nor intensity).

Therefore, I am making an assumption that English would have greater pitch PVI means than Spanish. From the graph of New Zealand English speakers provided in Nokes &

Hay (2012:19), it appears that the average is between .15 and .20, which does indicate more variability than the Spanish of the speakers in the current study. However, to make the findings in the current study truly comparable, the same method (i.e. PVI measurement) would have to be applied to English of the same region, and ideally of the same speakers.

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6.2.4 Intensity PVI Discussion

Languages make use of the acoustic correlates of stress differently. For example, in declarative sentences in Spanish (but not in Catalan), Ortega-Llebaria and Prieto (2007a) find that overall intensity is one factor that differentiates stressed syllables from unstressed syllables. Campbell and Beckman (1997) find that spectral tilt (the relative difference in intensity between the higher frequency and lower frequency regions of the spectrum) does not differentiate between stressed and unstressed syllables when there is no pitch accent in American English, although Sluijter et al. (1997) do find that spectral tilt (and duration) are strong correlates of stress in Dutch, more so than overall intensity.

Navarro Tomás (1964) claimed that the most prominent cue to stress in Spanish is an increase in intensity, but recent research suggests that the type of intensity measurement makes a difference. Ortega-Llebaria & Prieto (2007b) claim that spectral tilt, rather than overall intensity, is a better correlate of prominence and that when the pitch movement is flat, spectral tilt is a better indicator of stress in Spanish than overall intensity (Ortega-Llebaria & Prieto 2007b). Furthermore, the strongest acoustic correlates of stress in Spanish are duration and pitch, and spectral tilt and vowel quality provide further cues to indicate stress (Ortega-Llebaria & Prieto 2007b). Benevento (2017) also finds that overall intensity is not a reliable cue to indicate prominence because of almost imperceptible differences in absolute intensity between syllables, which fall below a threshold of discernibility (less than 3 dB), although intensity varies widely by speaker.

Future research should consider differences in spectral tilt across generations of New

Mexican Spanish speakers, as studies of Spanish find spectral tilt to be a more reliable cue to prominence in Spanish than overall intensity (Ortega-Llebaria & Prieto 2007b,

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Ortega-Llebaria & Prieto 2010). Furthermore, intensity is affected by recording procedures, and in the NMCOSS recordings, where the microphone was held in relation to the speaker was not held constant across interviews, which likely affected overall intensity measurements.

The primary research question asked whether there has been a change in New

Mexican Spanish prosody, possibly due to influence from English. Regardless of the specific intensity measurement and recording procedures used in this study, it may be the case that there has simply been no diachronic change in intensity variability in NMS.

Nokes & Hay (2012:18) were able to use the nPVI to effectively capture intensity differences in spontaneous speech from several corpora of New Zealand English. They find a significant increase in intensity nPVI with date of birth. They also use the nPVI formula to measure vocalic duration and pitch variability. In the case of English in New

Zealand, there has been a change from more stress-timed English to more syllable-timed

English, resulting in a decline in durational variability across ages, which may be due to influence from Maori, a syllable-timed language, and Maori English. In the case of New

Mexican Spanish, there has been no apparent-time change in rhythmic timing, which means that no compensation in intensity (or pitch) variability is necessary. Regardless,

Spanish Language Use correlates with intensity variability; this suggests that there may be a relationship between language proficiency (or confidence) and the speaker’s physical realization of various acoustic correlates of prominence, just as, for example, non-native speakers produce a narrower pitch range in second language speech (Backman

1979, Kelm 1995). In other words, as a speaker becomes more proficient in a language, his or her use of the range of various language-specific prosodic variables available to

225 him or her increases. This would be an interesting area to explore for future research. One problem with this, however, and with the discussion in the previous section on Pitch and

Age, is that proficiency was not coded for directly in this study, and the various factors of language use, age, and confidence are multifaceted and are not a substitute for proficiency; that is, any speculation here on why Spanish Language Use results in increased intensity variability (or why age correlates with decreased pitch variability) is just that – speculation. Future research should tease apart age, language use, dominance, and proficiency to elucidate how acoustic correlates of prominence differ depending on speaker characteristics, and why this may be. Unfortunately, this is not possible with the

NMCOSS, since much of this information was not recorded7.

Nokes and Hay (2012:20) found that males and females used intensity and pitch variability to mark prominence in stressed syllables differently; as durational variability decreased, earlier-born males were found to use intensity PVI to a greater extent to mark prominence, whereas later-born females used pitch to a greater extent. In the current study, no such difference by gender was found. The research question asked how pitch, intensity, and duration become more or less variable in relation to each other. One interesting trend was found regarding Wealth. For pitch, the greater the wealth, the more variability in pitch is likely across consecutive vowels, a significant effect. Meanwhile, the trend for intensity, although non-significant, is in the opposite direction: the higher the wealth, the less likely speakers are to exhibit variability in intensity across successive vowels. I speculate that as pitch becomes more variable (and therefore more important for

7 Spanish and English proficiency were self-assessed and assessed by interviewers on a scale from 1-5 in the NMCOSS. However, this rating was highly subjective as there was no assessment tool to determine the rating, and interviewers differed greatly on how they rated subjects. Therefore, I do not consider this a reliable proficiency scale.

226 signaling prominence), intensity becomes less so. Furthermore, as speakers learn English later, their intensity PVI decreases, but the opposite occurs for pitch PVI. It is interesting, therefore, to ask why pitch and intensity exhibit opposite tendencies for certain variables.

Little is known about the relative contribution of intensity to prominence, and even less is known about intensity measured in PVI and how that varies along social dimensions.

Therefore, this study is a first step in demonstrating how pitch and intensity vary across successive vowels and how that variation correlates with social variables, but there are still unanswered questions regarding intensity PVI that remain to be explored in future studies.

In sum, the positive correlation between Spanish Language Use and mean

Intensity PVI signifies that the more Spanish used daily, the greater the mean intensity

PVI. It is possible that highly proficient and confident speakers make use of loudness to a greater extent as a cue to prominence than less proficient speakers. Future research should consider how intensity patterns along with other acoustic correlates of prominence in a tightly controlled recording environment, while accounting for factors such as proficiency and language usage.

6.2.5 Prosodic Hierarchy

Regarding part (d) of Research Question #1, whether there is a prosodic hierarchy in terms of the susceptibility of different prosodic variables to change, all prosodic variables considered in this study were resistant to change, which makes the answer inconclusive based on these data.

Thomas and Ericson (2007) find that while rhythm in terms of syllable and stress-timing clearly separates Anglos and Mexican Americans, young Mexican Americans produce a wide range of

227 values regarding the intonation variable in their study (“rising pitch prominence”), with some speakers producing Anglo-like values. Robles-Puente (2014) also finds a difference between rhythm and intonation regarding the influence of English on L.A. Spanish. He finds that rhythm in the Spanish community becomes more stress-timed as speakers spend more time in the United

States and have more exposure to English. However, Spanish intonation remains resistant to change, although there appears to be some influence of Spanish in the intonation of English-

Spanish bilinguals. Specifically, rather than finding early alignment in Spanish pre-nuclear broad focus declarative pitch accents, he finds delayed alignment in English productions. Therefore, previous research considering both intonation and prosody in Spanish communities in the U.S. provides evidence that rhythmic timing patterns are more susceptible to change (or borrowing) than intonation in contact settings. Situations where interference (rather than borrowing) plays a role would likely find intonation and rhythm to be affected differently. Specifically, in the cases described above where borrowing occurs, rhythm seems more likely to change than intonation.

In a situation of interference, on the other hand, intonation seems highly susceptible to change when considering studies of alignment on Spanish pitch accent patterns (e.g. O’Rourke 2005,

Michnowicz & Barnes 2013).

Another way to get at the question of how different prosodic variables change in relation to each other is to ask whether the speakers in this study who displayed English-like characteristics did so for more than one variable. In other words, is there a correlation between the dependent variables? In fact, there is a significant negative correlation between speakers’ mean Rhythm PVIs and their mean alignment scores (Spearman’s rank correlation rho = -0.2950, p < .05). In other words, higher durational PVIs (i.e. on the more stress-timed end of the continuum) significantly correlates with lower mean alignment scores (i.e. more English-like).

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That is, speakers with more English-like means in one variable are likely to have English-like means in the other variable. Figure 48 displays a scatterplot of mean alignment scores with mean durational PVIs.

Figure 48. Speaker mean alignment scores plotted against speaker mean durational PVIs. The blue line is the regression line and the red line is the LOWESS (Locally Weighted Scatterplot Smoothing) line.

What this correlation tells us is that there is a relationship between rhythmic timing and intonation and that speakers who do show evidence of English influence in one area also show evidence in the other. What is unclear from the analyses, however, is what social variables define these speakers, since they do not pattern in any clear way from the independent variables considered in this study. In other words, the speakers with low mean alignment scores are not necessarily younger speakers, nor those who acquired English early. However, we do know that

229 females with more years of education are more likely to exhibit more stress-timed Spanish, which may give us a clue to the members of this speech community who may open the door to

English patterns in their Spanish.

In sum, the dependent variables considered in this study (pitch peak alignment, rhythmic timing, and pitch and intensity variability) do not exhibit change in apparent-time, in spite of the long-term contact and bilingualism with English in New Mexico. Though little can be said in terms of a prosodic hierarchy of the susceptibility of various prosodic factors to change in a contact setting, we do know that the speakers who exhibit more stress-timed Spanish also exhibit earlier alignment. This suggests that multiple facets of prosody can be affected by contact in tandem. To the extent that the speakers who display the highest durational PVI values and the lowest alignment values receive these non-typical values because their Spanish prosody has been influenced by English, this suggests that, while in general the phonology of the speech community has not been affected by English, there is a subset that has.

6.3 Null hypothesis

The hypotheses presented in Research Questions #1 and #2 predicted English influence on NMS intonation. The null hypothesis predicted that there would be no differences among speakers by age, and this was borne out by the findings. In the case that apparent- time effects of prosodic change would not be found, I asked:

3. What is it about the language situation in NMS that has inhibited prosodic change, which is known to be highly susceptible to influence in contact situations?

I hypothesized that if there were no apparent-time effect indicating prosodic change, then prosody has remained relatively stable in NMS throughout the 20th century.

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In this case, the unique prosodic patterns that make NMS stand out as a distinct variety could either be due to (1) features that were already in place pre-widespread English bilingualism, in which case the oldest speakers would exhibit the features, or (2) unique prosodic features that have indeed developed in NMS, but are features which are not considered quantitatively in this study. While we cannot say anything about the latter case, in the former case we would assume that NMS has remained relatively impervious to English influence, a result which has been found in several studies of NMS (Torres

Cacoullos & Travis 2011, Benevento & Dietrich 2015, Balukas & Koops 2015). In this case, speakers exposed to two prosodic systems are able to maintain a monolingual-like

Spanish phonology.

Rhythmic timing is affected by phonological characteristics of the language, such as syllable structure and reduction of unstressed vowels. These characteristics of NMS were not considered in this study, but there is no reason to think they have changed in

NMS, and studies of the grammar and phonology of NMS have not found change attributed to English. Since durational timing has not changed, there is no reason to think that other correlates of prominence would change either. Silva-Corvalán (1994) claims that changes due to a contact language are indirect and are merely an acceleration of changes already in progress in the receiving language. In the case of peak alignment, early alignment is already present in Spanish in narrow focus contexts, which is possibly why alignment patterns in broad focus contexts have been found to change in various other contact settings (e.g. O’Rourke 2005, Michnowicz & Barnes 2013, Elordieta 2003).

However, this change does not seem as likely to occur when Spanish is the L1 and the language with early alignment patterns is the L2, as is the case of Spanish in the United

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States. In other words, what differentiates Quechua Spanish in Peru from New Mexican

Spanish, for example, is that Spanish is the L2 in Peru (and hence the situation is characterized by interference, rather than borrowing), but not in the United States. This could be why Alvord (2006) and Robles-Puente (2012) also do not find early alignment in the Spanish of their speakers.

The results from this study demonstrate that contact with English is not enough for the prosodic system of Spanish to change. Why has New Mexican Spanish not experienced more influence from English? L.A. Spanish, Miami Spanish, Texas Spanish, and North Carolina Spanish all found influence from English in their prosody, albeit to different extents depending on whether the prosodic feature in question was rhythm or intonation (Robles-Puente 2014, Enzinna 2015, Carter & Wolford 2016, Carter 2005,

Thomas & Carter 2006). The social characteristics of the New Mexican Spanish speech community must be considered here, since social factors, as much as or possibly more than linguistic factors, affect what features are susceptible to contact effects and to what extent in language contact situations (Thomason & Kaufman 1988). Shin and Van Buren

(2016) ask a similar question regarding a bilingual Mexican American community in the

Pacific Northwest. Their study finds no evidence of change in grammatical patterns of

Spanish subject pronoun expression, in spite of evidence of change in other Spanish communities in the U.S. (e.g. Otheguy & Zentella 2012). Shin and Van Buren (2016) find that, like in New Mexican Spanish (Torres Cacoullos & Travis 2011), rates of subject pronoun expression as well as patterns conditioning pronoun use are maintained in the productions of bilingual children in this community. They draw upon social network theory to explain why Spanish patterns are maintained in this community in particular,

232 which can be extended to explain what is happening in New Mexican Spanish. They claim that rural, poor communities are more likely to be characterized by tight-knit social networks, which are known to be norm-enforcement mechanisms (Milroy 1987). The connection between maintenance of Spanish patterns and socioeconomic status is supported by findings in New York Spanish (Shin & Otheguy 2013), which demonstrates that the Spanish communities in New York most likely to produce increased pronoun expression rates are more wealthy communities (Colombians and Cubans). The converse is also true; that is, the poorest communities see the least amount of change (Mexicans and Dominicans, with the exception of Ecuadorians who see change but are midway on the affluence scale). The presence of tightly integrated social networks could explain why

New Mexican Spanish has remained seemingly impervious to English influence, apart from the lexicon.

The youngest speakers in the sample chosen for this dissertation study were born in the 1970s, when Spanish was still being learned as the first language by a majority of

New Mexicans of Spanish heritage (81%) (Kravitz 1985:28), which is remarkable, considering how long English had been in the state and the “official opposition” Spanish speakers faced by the local government. According to Solé (1990:53), Mexican

Americans in the Southwest have historically been able to maintain “strong ethnic boundaries” and are thus heavily concentrated in particular areas. Furthermore, the mostly homogenous communities are characterized by low educational and occupational levels. In other words, the profile of Traditional New Mexican Spanish speakers fits the same as the community of Mexican Americans in the Pacific Northwest who maintained

Spanish patterns shown to change in other U.S. Spanish communities (Shin & Van Buren

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2016). In fact, the authors make this connection between the two communities.

In sum, this and other studies analyzing English influence on New Mexican

Spanish have found that the grammar and phonology of New Mexican Spanish is resistant to change from English (Torres Cacoullos & Travis 2011, Benevento & Dietrich

2015, Balukas & Koops 2015, Bills & Vigil 1999). This resistance is likely due to sociodemographic characteristics and possibly identity factors. Indeed, Solé (1990:53) notes that Spanish language maintenance does not correlate well with education, occupation, and income, factors traditionally considered in sociolinguistic studies.

Rather, important to Spanish language maintenance are “the community milieu, the geographic contiguity and demographic concentrations of the minority population, their segregation from the mainstream society, and the strong ethnic boundaries among their fellow ethnics” (Solé 1990:53). Perhaps Solé’s claim can be extended to include borrowing or external influence; that is, the likelihood of contact-induced change should take into account community characteristics such as the concentration of minority speakers in a given area, social networks, language attitudes, and identity. It is possible that the use of New Mexican Spanish and NMS norms have covert prestige which lend a positive attitude toward speaking non-English influenced Spanish. Furthermore, the reinforcement of monolingual Spanish norms via continued immigration of Mexican

Spanish speakers has likely been an additional factor in maintaining monolingual Spanish patterns in this community. It is possible, for example, that the younger and middle speakers in my sample show few English effects because they oriented in part towards

Mexican Spanish-speaking peers in their acquisition of Spanish prosody.

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6.4 Future Research

Given that alignment and rhythm were found to be within the expected range for Spanish monolingual varieties, what is it that makes NMS prosody stand out? There remains the obvious possibility that NMS has a unique prosody, but either (1) the variables analyzed in this study did not capture it or (2) the speech sample studied did not contain the variation. Since the NMCOSS interviews were collected in the early 1990s, there is a possibility that the unique prosody heard in the community is a recent urban phenomenon of the latest generation who has had the most exposure to English. However, this is unlikely as Hills (1906) already reported that NMS had a unique intonation (which he ascribed to indigenous influence), signifying that NMS has possibly had a unique prosody since the early 1900s. Furthermore, Benevento (2017) found the delayed pitch accent pattern to be common in her sample of the NMSEB, a corpus of NMS interviews recorded between 2010-2011 (Travis & Torres Cacoullos 2013). Therefore, it is not likely that early peak alignment patterns have developed in the youngest generation born after the 1970s.

Unique prosodic features not attributed to English could be an innovation occurring after isolation from other Spanish-speaking communities. This is not far- fetched; for example, Bullock (2009:165) notes that change occurs in linguistic minority communities as a result of removal from standardization pressures of literature and education and that the “phonological system transmitted to heritage speakers may be different from its source variety purely by virtue of its oral transmission through several generations.” New Mexico remained isolated for three hundred years; throughout this time, traditions were passed down generation to generation orally. During my analysis, I encountered a unique prosodic feature; this characteristic was mainly restricted to a salient boundary tone and was heard in the middle and older speakers, with the exception

235 of one 34-year-old male speaker, the youngest speaker who produced it. This boundary tone was likely similar to what Lipski (2011:88) claimed characterized northern New

Mexican and northern Mexican intonation and which he claims forms “the basis for the stereotypical "Mexicano" accent in countless movies, radio and television programs, and comedy routines.” The pattern Lipski described has a long rise throughout the lengthened nuclear syllable, and peaks within the nuclear syllable. Rather than being followed by a low boundary tone (L%), typical of Spanish declaratives, these “Norteño” declaratives end in a high boundary tone (H%). In the case of my sample, twelve speakers occasionally produced a rise throughout the nuclear syllable which peaked within the syllable, with a sustained pitch on the post-tonic syllable that ended in a mid- (M%) (see

Figure 52) or more frequently high (H%) (see Figure 49, Figure 50, and Figure 51) boundary tone. What makes this feature especially unique is that the post-tonic syllable

(not the nuclear syllable) in the final foot is lengthened, typically with the sustained pitch throughout, and sometimes with a sharp fall at the end of the phrase (see Figure 53). This post-tonic lengthening was not mentioned in Lipski (2011) but is salient to listeners. The following pitch tracks from the interviews display this salient post-tonic lengthening and boundary tone.

236

237

Figure 50. Example of salient final post-tonic lengthening and sustained H% boundary tone in the phrase Antonio Lopez. The example is from Interview 145, a 50-year-old male speaker from Pecos, NM.

Figure 51. Example of salient final post-tonic lengthening and sustained H% boundary tone in a declarative utterance, pues esta la conocí en un baile ‘Well I met this one at a dance’. Interview 214, 76-year-old male speaker from Ojo Feliz, NM.

238

Figure 52. Example of salient final post-tonic lengthening and sustained M% boundary tone in the declarative utterance de demasiado importancia ‘of utmost importance’. Interview 118, 59-year-old male speaker from La Loma, NM.

200

)

(

0 F

Me acuerdo una vez que tiramos toda la tierra a la azotea

F F

me acuerdo una vez que tiramos toda la tierra a la azotea

0 2.499 Time (s)

Figure 53. Example of a rise in the nuclear pitch-aligned syllable and followed by a sharp fall into a lengthened post-tonic syllable in the declarative utterance Me acuerdo una vez que tiramos toda la tierra a la azotea ‘I remember one time we through all the dirt at the roof’. Interview 118, 59-year-old male speaker from La Loma, NM.

239

Twelve speakers in the sample, ranging in age from 34-83 (mean = 56.75, median =

56.5), produced this post-tonic lengthening and boundary tone. Nine producers were males, three were females. Note that the post-tonic lengthening only occurs in the final foot. Speakers who produce this pattern do not produce it frequently, but when they do, it is salient as a dialectal marker. The pragmatic usage driving the production of this boundary tone remains unknown. This is an area that should be investigated in future research.

In addition, future research should analyze the variables considered in this study in the English of the same speakers. The NMCOSS interviews contain a small portion of conversation in English, included for the interviewer to gain an idea of the speakers’

English proficiency. Studies of Spanish communities in the U.S. have found evidence of

Spanish influence in the prosody of Hispanic English (Robles-Puente 2014, Carter 2005,

Fought & Fought 2002, Thomas & Carter 2006) and this may be the case in New Mexico as well.

Finally, as mentioned in the previous section, future research should tease apart age, language use, dominance, and proficiency to elucidate how other sociolinguistic variables correlate with the production of various acoustic correlates of prominence, and why this may be. In addition, although using spontaneous speech allows us to analyze prosody naturalistically, which is ideal from a sociolinguistic standpoint, it would be desirable to compare these results with controlled speech, in order to be able to ensure that my results are compatible with laboratory studies.

240

6.5 Limitations

As pointed out previously, this study only considers the Spanish of the speakers in this subsample without considering their prosodic productions in English. Future research would benefit from such an analysis. Furthermore, because of this limitation any findings on prosodic change in NMS can be only indirectly attributed to English. The NMCOSS itself, while providing a wealth of lexical information, was not intended to capture the type of variation that tracks language shift patterns. In other words, speakers were included on the basis of representing the most “authentic” Traditional New Mexican

Spanish, and are not a random sample of New Mexican Spanish speakers. Furthermore, recording procedures varied widely by interviewer, and since the aim of the corpus collection was to create a Linguistic Atlas, conversation in some cases is minimal.

Furthermore, conversation in the NMCOSS interviews is at times formal and stilted, which likely affected the realization of the prosodic variables considered in this study.

Benevento (2017:183) uses another corpus of New Mexican Spanish, the NMSEB, and claims that the conversations were lively and narrative-rich, which resulted in a high number of lexical items being produced with pitch accents. This was not the case in the

NMCOSS, where finding enough pitch accented syllables in a five-minute stretch of speech was challenging and the samples of Spanish conversations could not generally be considered “lively”. This was surprising, given that almost every lexical item is supposed to be pitch accented in Spanish (Hualde 2002). Furthermore, many younger and middle- aged speakers had difficulty maintaining conversation in Spanish.

Additionally, the lines between Traditional New Mexican Spanish and Mexican

Spanish are not always clear-cut. Even though speakers were included in the sample

241 based on producing a majority of Traditional NMS lexical responses, Mexican Spanish forms were still frequent throughout conversations. For example, a 73-year-old male from Costilla (population: 205) uses chamaca for ‘girl’, rather than the Traditional term plebe, and a common Mexican slang term a la chingada (Interview 156). Another speaker, a young male from Albuquerque, uses zanjita for ‘irrigation ditch’ rather than the traditional NMS acequia (Interview 32). This same speaker also produced chamaco for ‘boy’. These examples demonstrate that terms such as “New Mexican Spanish” and

“language contact” are used as if they constitute a uniform reality, but the actual make-up of this speech community is far more complex and multifaceted, as is the situation of bilingualism with English and dialect contact with Mexican Spanish.

6.6 Conclusion

This dissertation study has analyzed prosodic variables in New Mexican Spanish, using the apparent-time construct as a basis to determine whether there has been change throughout the twentieth century, possibly due to increased influence from English. The main finding of this study is that, at least with regards to the prosodic variables analyzed which differ between Spanish and English, the prosodic system of NMS has remained resistant to change, a finding that is corroborated by other studies of New Mexican

Spanish (Benevento 2017, Torres Cacoullos & Travis 2011, Balukas & Koops 2015,

Benevento & Dietrich 2015, Bills & Vigil 1999). While this study provides a glimpse into the NMS prosodic system, there is still much left to investigate, such as the inventory of pitch accents in nuclear position of broad focus declaratives which may include a pattern unique to NMS, as described in Section 6.4. The intonation of NMS remains to be

242 fully described; other utterances such as interrogatives and imperatives should be investigated, and a full account of pitch accents in broad focus declaratives also needs to be investigated (although see Benevento 2017). Such an analysis may be aided by an analysis of controlled speech in a laboratory setting. A more complete description of

NMS intonation would also include an analysis of pitch accents in different focus contexts.

This study provides one of the first acoustic intonational analyses of NMS. In addition, this study informs language contact studies in general and intonation in contact specifically. The NMCOSS corpus is unique in that the speakers’ birth years span the exact century that saw increased contact with English throughout the state of New

Mexico. Therefore, apparent-time data are available that allow us a glimpse into changes in intonation through a long-term contact situation. Bilinguals’ performance in such long- term language contact situations has been understudied, as have the consequences of long-term contact on phonology, and specifically, on intonation (Bullock 2009:167). This study adds to the understanding of such consequences on the borrowing of prosodic variables. It has been shown that change in one prosodic variable can occur in tandem with change in another variable.

This study is also informative as to the role of L1 and L2 languages on intonation in contact. Cases reported in the literature on contact-influenced Spanish intonation

(frequently on peak alignment) tend to focus on cases where Spanish is the L2 language whose phonology is affected by substratum languages, such as Quechua (O’Rourke 2003) and Basque (Romera & Elordieta 2013). In other words, interference plays a role in such situations (Thomason 2001). However, in New Mexico, L1 Spanish speakers have

243 learned English to varying degrees. The results of this study suggest that intonation, in particular alignment, is less likely to be susceptible to influence when L1 to L2 interference does not play a role in the contact situation. This is the difference between speakers being dominant in Spanish (e.g. New Mexico historically) and speakers of an L2 variety of Spanish that is influenced by their L1 (e.g. Quechua, Basque, Yucatec Maya).

This study also provides a foundation for intonational research on New Mexican

English. A future study would analyze prosodic variables in the English of the same participants in order to compare patterns. Are there more differences in the two languages in the older speakers than in the younger speakers? How does intonation in New Mexican

English compare with English spoken in regions of the U.S. without influence from

Spanish? In addition, this study sets a foundation for perception studies on intonation which are in their infancy. For example, what is the social significance of peak alignment

(and pitch range, and prosodic timing)? In other words, can community members tell by intonational variables alone the ethnicity or background of a speaker? How salient are peak alignment differences?

This study is among the first to use apparent-time data to track prosodic variables in a language contact setting, and the results have demonstrated that New Mexican

Spanish sits squarely within the prosodic norms for monolingual communities. The prosodic description provided in this study adds to our knowledge of Spanish intonation in general and of a variety of Spanish that has been previously understudied in particular.

This study has provided a picture of the situation of language contact between Spanish and English in New Mexico, and how this speech community has been resistant to change from English, suggesting that social factors should be considered along with

244 linguistic factors when discussing prosodic change in contact situations. In sum, this dissertation has added to the field of prosody studies in language contact situations and is a point from which future studies of prosody in New Mexican Spanish and other varieties of Spanish in the U.S. can develop.

245

Appendix A. Speaker PVI Results

Speaker Age Durational Duration Mean Mean Mean Mean PVI Mean PVI Average Midpoint PVI Intensity Median Pitch Pitch Max PVI PVI PVI Pitch 1 52 0.364 0.309 0.1 0.11 0.098 0.06 2 56 0.361 0.299 0.07 0.08 0.066 0.05 3 52 0.43 0.355 0.061 0.065 0.064 0.057 5 63 0.372 0.327 0.067 0.071 0.066 0.047 7 82 0.345 0.272 0.085 0.09 0.086 0.039 8 78 0.37 0.305 0.044 0.047 0.051 0.05 9 29 0.402 0.374 0.036 0.036 0.046 0.045 15 39 0.332 0.236 0.041 0.044 0.045 0.059 19 29 0.393 0.34 0.046 0.046 0.049 0.047 25 41 0.361 0.311 0.132 0.138 0.142 0.045 29 27 0.419 0.356 0.039 0.041 0.044 0.049 32 34 0.318 0.281 0.06 0.064 0.059 0.057 36 25 0.411 0.33 0.053 0.055 0.058 0.052 37 40 0.415 0.325 0.066 0.071 0.065 0.051 41 56 0.341 0.302 0.103 0.104 0.1 0.055 43 34 0.42 0.359 0.048 0.051 0.048 0.04 44 73 0.317 0.266 0.06 0.063 0.055 0.041 50 74 0.39 0.345 0.074 0.078 0.087 0.037 63 29 0.273 0.266 0.06 0.06 0.063 0.044 67 45 0.342 0.296 0.049 0.05 0.051 0.043 70 58 0.444 0.413 0.098 0.104 0.107 0.05 73 66 0.348 0.286 0.077 0.077 0.092 0.063 81 87 0.308 0.308 0.082 0.087 0.086 0.055 89 57 0.392 0.313 0.042 0.053 0.055 0.056 91 44 0.286 0.24 0.047 0.049 0.06 0.033 101 37 0.337 0.299 0.084 0.088 0.075 0.039 103 34 0.343 0.29 0.033 0.033 0.046 0.051 105 32 0.296 0.229 0.046 0.052 0.055 0.035 107 56 0.352 0.296 0.073 0.076 0.075 0.041 108 83 0.359 0.299 0.082 0.087 0.089 0.049 118 59 0.309 0.24 0.079 0.087 0.085 0.028 127 48 0.292 0.286 0.06 0.059 0.074 0.043 142 80 0.334 0.288 0.065 0.068 0.069 0.055 144 83 0.36 0.306 0.09 0.094 0.089 0.034 145 50 0.349 0.3 0.091 0.094 0.091 0.033 152 29 0.369 0.251 0.068 0.076 0.059 0.039 154 41 0.333 0.313 0.057 0.06 0.057 0.071

246

156 73 0.352 0.293 0.062 0.066 0.055 0.048 157 38 0.357 0.303 0.056 0.057 0.057 0.048 202 21 0.359 0.305 0.071 0.072 0.08 0.047 208 27 0.397 0.33 0.041 0.042 0.042 0.043 209 23 0.396 0.36 0.1 0.099 0.092 0.053 214 76 0.397 0.325 0.045 0.045 0.046 0.049 215 75 0.337 0.282 0.074 0.077 0.071 0.051 220 23 0.428 0.4 0.075 0.083 0.059 0.042 221 27 0.39 0.348 0.048 0.051 0.051 0.056 222 55 0.334 0.273 0.066 0.072 0.064 0.048 230 44 0.403 0.328 0.059 0.06 0.061 0.043 232 36 0.376 0.295 0.074 0.078 0.074 0.056 234 64 0.353 0.325 0.076 0.078 0.081 0.043 238 45 0.325 0.24 0.066 0.066 0.076 0.048 241 73 0.363 0.304 0.078 0.08 0.078 0.046 246 76 0.363 0.256 0.056 0.057 0.069 0.047 271 79 0.381 0.291 0.069 0.073 0.074 0.072 272 95 0.335 0.248 0.067 0.073 0.079 0.053 279 59 0.366 0.321 0.063 0.072 0.065 0.033 289 41 0.335 0.318 0.056 0.058 0.057 0.06 306 66 0.406 0.345 0.082 0.084 0.074 0.046 353 60 0.315 0.241 0.062 0.063 0.056 0.049 361 18 0.394 0.316 0.063 0.066 0.059 0.047

247

Appendix B. Speaker Alignment Results

Speaker Age Mean Median Standard Median Alignment Alignment Deviation Absolute Score Score Standard Deviation 1 52 99.206 112.5 73.899 83.396 2 56 133.998 130.3 65.326 66.495 3 52 92.063 86.7 75.244 90.883 5 63 111.573 117.5 68.511 61.973 7 82 98.486 91.5 62.298 60.49 8 78 109.231 98.6 78.963 106.599 9 29 83.478 62.3 74.967 91.032 15 39 120.819 124.9 94.815 111.862 19 29 104.206 112.7 84.496 108.675 25 41 124.618 144.5 84.912 68.496 29 27 100.559 92.2 106.028 96.517 32 34 125.384 136 70.943 75.761 36 25 110.962 128.7 94.144 132.248 37 40 124.722 125.7 86 101.113 41 56 116.711 124 66.787 73.389 43 34 124.135 138.8 68.602 32.321 44 73 128.734 142.1 82.221 68.422 50 74 81.42 86.9 57.808 70.349 63 29 93.478 82.9 62.51 65.605 67 45 109.939 102.3 87.428 82.581 70 58 112.686 104.3 86.18 75.168 73 66 103.432 111.8 80.697 111.417 81 87 128.738 133.8 73.572 44.181 89 57 116.858 129.1 75.493 60.638 91 44 113.022 145.5 90.562 111.047 101 37 150.467 159.7 88.291 59.304 103 34 137.914 133.9 82.476 78.281 105 32 125.16 158.8 90.004 85.324 107 56 89.194 96.5 70.504 62.862 108 83 93.07 85.1 76.153 99.26 118 59 123.524 137.7 79.622 90.809 127 48 158.464 157.3 97.746 75.39 142 80 131.166 146.5 73.828 67.903 144 83 146.62 102.7 346.926 72.796 145 50 110.467 122.2 58.449 59.452 152 29 123.867 136 82.08 88.141 154 41 102.646 74.5 80.468 103.782

248

156 73 82.498 71.4 55.889 59.971 157 38 91.848 48.2 103.031 69.83 202 21 102.294 89.8 84.374 107.933 208 27 97.133 87.7 78.155 102.151 209 23 84.696 68.1 71.92 92.44 214 76 129.914 133.6 59.583 48.036 215 75 114.858 124.2 72.265 61.083 220 23 78.428 28.9 96.182 44.256 221 27 83.874 71.6 70.85 93.7 222 55 120.198 120.4 85.725 109.416 230 44 128.164 34.8 78.59 78.059 232 36 103.406 90.9 73.36 55.82 234 64 73.434 43.6 78.938 63.01 238 45 101.332 89.3 86.035 89.104 241 73 111.539 118.9 69.96 64.641 246 76 102.212 114.6 77.125 114.16 271 79 76.978 74.3 52.305 53.818 272 95 105.966 127.1 76.091 82.581 279 59 129.896 128.2 74.214 47.369 289 41 120.814 146.2 79.782 72.203 306 66 103.566 116.4 74.513 73.685 353 60 143.245 142.8 75.056 35.434 361 18 138.456 133 87.439 52.632

249

Appendix C. Peak Alignment Linear Regression Random Effects

1. Main Regression with all tokens included.

Random Effect: Speaker

Speaker Intercept Tokens Mean

16.086 2932 109.436

1 1.281 45 107.189

2 19.2 48 139.236

3 -16.598 51 95.82

5 3.177 50 130.375

7 -6.759 51 100.456

8 -4.346 50 106.012

9 -17.391 49 83.312

15 6.633 51 124.158

19 -6.811 49 97.74

25 14.319 50 129.3

29 -14.359 50 87.767

32 8.796 49 118.875

36 0.006 50 113.227

37 14.645 49 127.267

41 5.392 45 105.034

43 10.013 51 204.223

44 3.625 47 122.665

250

50 -19.446 50 84.812

63 -19.33 49 91.426

67 -1.913 47 102.815

70 -6.44 46 91.726

73 -6.037 48 100.71

81 14.768 47 113.49

89 0.109 49 121.587

91 2.166 49 110.004

101 25.719 47 136.943

103 26.159 49 138.174

105 5.033 50 130.375

107 -13.371 50 98.913

108 -8.563 50 94.969

118 13.949 50 123.524

127 32.344 48 146.594

142 22.105 50 131.166

144 -6.497 48 92.892

145 -2.283 51 112.676

152 13.388 49 123.866

154 -9.913 49 101.424

156 -14.326 50 82.498

157 -4.079 31 55.829

202 -6.661 50 102.294

251

208 -7.252 49 97.114

209 -19.215 50 88.465

214 16.388 50 129.914

215 -1.995 51 115.214

220 -29.37 48 63.165

221 -17.787 50 93.193

222 6.01 51 120.198

230 12.876 50 136.345

232 -9.255 48 89.016

234 -22.343 47 69.028

238 -4.698 49 100.82

241 -0.514 50 113.055

246 -2.906 50 102.212

271 -23.17 50 83.672

272 -1.357 50 109.308

279 14.036 50 129.896

289 3.077 50 125.438

306 -4.414 50 105.68

353 16.285 49 134.388

361 17.905 49 131.731

252

2. Main Regression with voiceless tokens and closed tonic syllable types

excluded. Random Effect: Speaker

Speaker Intercept Tokens Mean

15.947 968 123.439

1 -7.093 16 115.412

2 7.222 14 106.563

3 -16.598 51 95.82

5 10.038 11 85.953

7 -7.853 14 73.7

8 -1.518 13 110.721

9 -14.684 16 128.342

15 6.359 13 134.469

19 9.946 12 101.424

25 9.975 19 189.971

29 -5.922 16 65.541

32 5.278 11 113.892

36 10.312 13 163.175

37 7.96 16 128.129

41 -8.472 17 125.693

43 11.222 21 422.5

44 3.713 17 194.417

50 -17.615 16 100.964

63 -11.454 21 181.258

253

67 -0.013 18 173.485

70 -4.747 18 132.306

73 -11.536 16 104.853

81 7.721 20 100.867

89 -3.862 19 204.291

91 23.746 19 125.264

101 5.941 19 202.3

103 18.01 18 230.292

105 8.894 19 201.262

107 1.865 21 265.65

108 -10.706 14 66.038

118 -6.089 12 65.255

127 30.892 13 154.55

142 18.134 17 137.263

144 2.282 14 79.264

145 0.149 27 217.72

152 2.507 12 92.088

154 -2.479 17 114.989

156 -14.549 14 83.756

157 -15.022 7 26.463

202 11.76 12 167.364

208 -14.16 13 108

209 -15.122 16 74.515

254

214 0.276 15 142.385

215 -5.734 27 254.725

220 -19.16 11 51.625

221 -11.154 25 155.794

222 4.266 13 83.31

230 3 12 91.235

232 -5.808 13 130.073

234 -8.731 10 61.125

238 -7.55 21 112.476

241 -0.904 20 137.839

246 11.568 16 170.671

271 -19.875 22 105.511

272 7.408 15 130.588

279 10.216 17 180.431

289 -0.727 18 111.815

306 -13.847 11 52.047

353 15.346 20 192.137

361 16.83 12 103.495

255

3. Main Regression with all tokens. Random Effect: Word, ordered by intercept.

Word Intercept Tokens Mean Word (ctd) Intercept Tokens Mean ... 16.297 2932 109.436 correr 0.357 1 116.7 hace 31.014 13 223.915 señores 0.353 1 135.9 ese 27.262 7 238.314 señoras 0.35 1 127.2 esposo 23.542 5 225.14 estudie 0.348 2 121.3 papa 19.397 14 145.593 misma 0.347 2 84.75 carro 17.856 6 164.35 sangre 0.337 1 94.8 casi 16.052 15 152.84 abuelito 0.336 1 174.1 muchas 15.728 10 188.5 primaria 0.318 1 95.5 juntaban 15.673 4 175.775 estricto 0.304 1 120.3 nosotros 15.571 16 157.731 agua 0.3 6 128.083 puse 15.466 2 284.35 entender 0.29 1 148.7 gente 14.984 24 114.117 arboles 0.273 2 112.05 hermana 14.95 10 167.07 muchito 0.243 1 128.9 era 14.811 34 147.256 ignoran 0.239 1 141.1 comencé 14.532 2 222.95 estaría 0.238 1 116 mucho 13.848 23 162.387 hablábamos 0.23 4 151.275 padre 13.735 6 119.55 primera 0.222 1 131.3 cosa 13.338 12 150.617 plebe 0.221 2 100.75 hablaban 13.166 5 166.34 pueda 0.203 3 93.7 caja 12.889 3 228.467 vinieron 0.202 2 127.75 parte 12.409 8 128.1 treinta 0.191 2 75.7 este 11.995 8 127.338 alfabeto 0.171 1 176.9 estamos 11.558 5 155.16 segunda 0.169 1 104.6 todo 11.287 10 126.11 tía 0.167 1 121.8 echa 11.262 7 189.386 comidas 0.166 1 125.8 todas 11.259 2 219.4 diferentes 0.138 4 127.175 otro 11.215 17 164.294 trato 0.117 1 132.3 haces 11.205 2 264.1 medicas 0.082 1 128.2 escuelas 11.188 3 179.4 pone 0.082 2 89.55 tiempo 11.027 15 107.953 inquieto 0.075 1 139.1 cuatro 10.932 11 135.782 quizás 0.054 2 78.1 noche 10.854 4 201.85 grande 0.044 1 106.6 tiene 10.771 19 112.379 cantamos 0.037 1 90.2 platicaba 10.67 1 289.7 jugamos 0.018 1 161.1 tenemos 10.331 12 149.133 recién 0.016 2 70.65 dicen 10.325 7 192.243 ejemplo 0.014 3 96.433 pienso 10.253 3 150.933 ladrón 0.009 1 89.4 cuídanos 10.023 1 281.6 seguido 0.002 1 133.1 puro 10.02 9 117.422 programas -0.007 1 112.6 depende 9.973 6 108.717 machucaba -0.012 1 87.5 usa 9.954 2 248.7 hueveras -0.013 1 126.3 quiera 9.906 6 129.467 nuca -0.02 1 142.5 están 9.831 3 157.067 gusta -0.028 15 92.62 esas 9.825 1 340.9 comenzaron -0.038 3 111.733 tortillas 9.68 1 300.1 contestar -0.04 1 76.8 andaban 9.385 2 225.05 podíamos -0.04 1 119.5 quede 9.383 1 330.8 resfríos -0.049 1 111.4 decían 9.272 9 120.567 ‘onde -0.059 6 81.55 hermano 9.208 6 163.267 dolores -0.064 1 131 alguna 9.077 13 138.077 duraba -0.076 1 136.2 única 8.933 4 185.075 poco -0.091 4 117.975 chile 8.741 1 242.4 operaron -0.13 1 113.9

256

condado 8.522 3 191.7 miro -0.15 3 134.567 nomas 8.423 10 140.73 agarrara -0.164 1 116.8 puso 8.377 1 273.4 mismo -0.177 8 93.4 bastante 8.202 2 155.4 adelante -0.179 2 125.75 caso 8.179 1 243.7 ayudar -0.184 1 96.4 ojo 8.176 2 241 tomar -0.192 1 129.2 pensaban 8.172 1 247.8 riñones -0.206 1 114.2 llevan 8.044 1 260.2 mismas -0.214 2 111.75 entonces 8.039 7 120.029 aprendieran -0.221 1 117.5 oído 8.005 2 192.45 levantamos -0.222 1 118.3 hablen 7.841 2 205.9 tomando -0.225 1 104.9 ella 7.805 21 139.448 aunque -0.251 1 135.9 parece 7.717 5 186.62 primer -0.264 2 103.5 tuve 7.669 8 135.938 señora -0.285 4 115.875 supieron 7.646 1 243.1 loma -0.29 1 117 buscar 7.609 1 254.9 mudo -0.29 2 114.75 atrás 7.595 3 146.9 leo -0.293 1 135.6 quitado 7.572 2 170.3 habían -0.315 4 118.075 riega 7.402 1 263.9 hojas -0.329 1 154.1 echas 7.327 1 282.5 podrido -0.334 1 118.6 trece 7.269 2 176.25 tirarla -0.402 1 83.7 calabacitas 7.23 1 247.6 llamamos -0.434 1 110 muchachas 7.153 2 189.15 verano -0.436 2 110.6 unos 7.153 3 191.6 perdí -0.454 1 148.8 sepan 7.119 1 244.4 regando -0.485 2 88.55 persona 7.095 5 123.28 mayor -0.488 4 97.8 establecieron 7.092 1 205.5 nombres -0.49 1 75.6 murió 7.066 6 156.467 amplio -0.491 1 121.3 algo 7.019 2 162.65 convino -0.492 1 128.3 ciencia 6.982 1 189.3 lengua -0.492 1 74.8 cabeza 6.955 2 229.05 enfermo -0.493 3 100.433 terreno 6.952 2 206.85 barbones -0.507 1 107.7 tiempos 6.939 4 130.375 tiramos -0.515 1 128.1 exámenes 6.917 1 234.6 debíamos -0.518 1 125 peso 6.83 1 237.1 Chamizal -0.52 1 44.6 asina 6.81 2 162.4 corta -0.524 2 86.95 dice 6.708 8 174.1 sonaba -0.539 1 94.1 eran 6.507 1 238.2 digamos -0.541 1 114.9 tocaba 6.332 1 223.8 comían -0.563 2 106.5 usaban 6.265 6 125.433 ano -0.566 9 122.3 quiza 6.252 2 168.05 movimiento -0.583 2 107 fueron 6.242 4 121.2 sobrino -0.586 1 131 esta 6.208 4 137.625 hora -0.592 3 106.267 viven 6.115 3 168.9 comíamos -0.609 1 109.2 maestros 6.09 1 218.6 ensenarlo -0.622 1 98.3 podemos 6.088 2 197.3 azotea -0.627 1 104.5 acabaron 6.058 1 229.9 anduviéramos -0.637 1 125.3 truchar 6.015 1 198.2 pasar -0.637 1 83.1 ocho 5.977 3 193.333 lugares -0.642 2 109.8 semana 5.943 4 160.525 comía -0.649 2 105.95 lado 5.921 1 242.4 saben -0.657 3 79.067 metió 5.921 1 223.3 nueva -0.674 1 120.3 llaman 5.894 1 229.4 levantaron -0.677 1 82.1 ellos 5.777 12 139.917 hubieran -0.694 2 109.9 hallaban 5.75 1 219.9 negrita -0.703 1 139.9 matado 5.641 1 215.7 siete -0.704 8 106.25

257

metiendo 5.588 1 144.7 entiende -0.779 4 64.8 chotearon 5.578 1 200 mero -0.799 1 118.3 pequeño 5.566 1 221.9 libro -0.801 7 124.2 mana 5.518 3 155.5 viéndolo -0.812 1 87 jugando 5.323 4 131.125 para -0.824 3 88.667 bolsa 5.296 1 222.2 viajado -0.836 1 56.2 empezaba 5.286 1 183.5 difícil -0.863 2 120.9 diente 5.175 2 170.3 curso -0.865 1 60.2 portáramos 5.142 1 192.9 español -0.874 23 99.557 católica 5.138 2 153.45 castigaban -0.882 1 82.8 tienen 5.13 7 108.771 veinte -0.888 2 97.05 dije 5.126 6 170.833 salimos -0.902 1 115.8 acequias 5.087 1 204.2 menos -0.926 1 106.7 llegaron 5.039 2 168.55 siguieron -0.927 1 90.5 paciencia 4.955 1 195.2 grados -0.928 1 87.9 niño 4.882 1 198 enfermedades -0.934 1 160.7 jugaban 4.865 1 183.2 hija -0.936 3 143.333 compusiera 4.844 1 159.9 derechos -0.948 1 132.1 seigo 4.766 2 173.45 picándole -0.96 1 57.9 otra 4.731 12 156.142 nadie -0.968 1 90.5 asisto 4.709 1 143 cantos -0.988 1 64.9 tosiendo 4.695 1 139.1 española -0.989 1 90.9 sale 4.686 3 129.3 viviendo -0.989 1 81.5 empecé 4.684 1 193 trapo -0.999 1 90 historia 4.669 5 114.42 siguientes -1 1 74.8 llevaban 4.664 1 206.7 querido -1.005 1 127.6 demasiado 4.656 1 196.8 gavilán -1.012 2 103.4 supone 4.65 2 127.9 anglos -1.03 1 87 vecino 4.629 1 173.2 prefieren -1.048 1 73.1 abuela 4.626 4 142.275 sabían -1.056 5 121.28 habla 4.62 12 134.683 rato -1.077 1 132.7 entre 4.609 3 154.467 cuidarnos -1.081 1 110.4 escribíamos 4.603 1 201.3 únicos -1.115 1 57.6 cartucho 4.562 1 215.9 curanderas -1.123 2 116.5 teníamos 4.557 10 143.36 hablaron -1.134 1 107.4 Sergio 4.535 1 171 vende -1.161 1 63.2 estuvimos 4.53 2 184.55 quiero -1.171 8 85.625 tufo 4.527 1 190.6 crece -1.177 2 102 usen 4.527 1 232.2 ensenaba -1.182 1 85.9 busco 4.519 1 195.8 escrito -1.184 1 121.3 mira 4.512 3 152.033 llamaban -1.184 1 100.5 trabajo 4.511 4 158.425 hoyito -1.199 1 142.5 rezaban 4.491 1 173.2 arriba -1.228 8 130.162 trigo 4.485 1 164.3 platicona -1.24 1 102 ponían 4.47 5 150.7 realmente -1.242 1 85.9 últimos 4.467 1 203.7 compañía -1.25 1 95.3 apenas 4.436 1 235.6 comienza -1.271 1 89.8 crecido 4.413 1 151.7 llegar -1.278 1 111.2 pegado 4.411 1 185.5 trabajaba -1.28 2 76.65 reganando 4.393 1 180.2 algunos -1.289 2 130.55 cómico 4.392 1 187.6 enoja -1.293 1 125.3 vinimos 4.392 7 153.5 guerra -1.294 1 117.2 matar 4.378 1 150.6 volteé -1.341 2 89.05 sido 4.374 2 115 único -1.359 4 110.55 partes 4.366 1 158.1 cambia -1.367 1 48.6 cuanto 4.336 1 167.9 broma -1.368 1 107.1

258

amigo 4.25 2 169.45 enfermaba -1.42 1 92.3 sacaban 4.245 1 183 creía -1.426 1 117.8 trabaja 4.221 3 166.3 cortar -1.427 2 71.6 acabo 4.218 1 193.4 agarrarlo -1.437 1 64.1 comencé 4.208 2 117.4 vuelvo -1.437 1 54.6 ojito 4.205 1 221.1 andando -1.481 1 84.5 pagaban 4.174 1 201.5 cerco -1.487 1 64.7 esos 4.151 1 215.1 acabamos -1.501 1 100.4 pescado 4.084 1 171.6 borregas -1.505 1 76.1 chicos 4.065 1 202.4 curandera -1.507 4 117.725 estando 4.059 1 134.2 mano -1.525 2 113.45 limpiando 4.036 3 106.367 vivir -1.592 3 85.033 importa 4.034 2 129.05 estado -1.593 2 78.5 entremedio 3.993 2 165.5 usan -1.599 3 130.133 explicar 3.93 2 105.75 entiendo -1.624 2 57.75 dejaba 3.914 1 176.9 crecí -1.625 1 78.6 íbamos 3.914 2 155.85 pasaban -1.627 1 40.4 cuidarse 3.909 1 187.9 cuenta -1.635 1 68.9 animales 3.863 4 147 empecé -1.68 2 106.4 perdido 3.845 1 190.7 comenzar -1.689 1 39.9 creen 3.82 1 185.2 tiendas -1.702 1 47.5 ido 3.76 2 180.5 nieve -1.704 1 84.6 cursos 3.745 2 122.25 corrales -1.705 1 119.1 afortunadamente 3.711 1 189.1 toda -1.742 9 76.822 fallo 3.69 1 133.2 leche -1.757 1 91.2 miraba 3.69 1 201.2 vendía -1.757 2 103.2 mataban 3.669 1 153.8 catorce -1.758 1 46.2 usábamos 3.647 1 157 usaba -1.761 1 53.6 casas 3.646 1 199.1 agarro -1.769 2 107.95 andar 3.637 2 144.9 leyendo -1.783 1 89.1 tapa 3.628 1 182.1 porque -1.794 12 83.167 pusimos 3.624 3 137.4 afuera -1.812 8 97.237 pegue 3.621 1 199.6 concepto -1.815 3 70.867 usaron 3.611 1 168.3 pegara -1.837 1 82.2 hago 3.604 1 171.5 usar -1.841 1 20.3 familia 3.599 3 145 camino -1.89 1 83.6 siembre 3.58 1 135.2 fuego -1.893 1 52 venir 3.573 1 207.8 decimos -1.903 1 56.9 decíamos 3.558 2 131.35 dinero -1.926 1 86.8 edad 3.533 2 138.2 nombre -1.935 2 75.5 creciendo 3.506 1 142.9 susto -1.942 1 51.6 comprendo 3.498 2 97.9 alfalfa -1.985 1 59.3 visto 3.491 1 155.5 estados -1.989 1 68.7 trabajando 3.484 2 112.4 enterramos -1.992 2 125.75 criados 3.462 1 182.2 nunca -1.999 14 114.243 creían 3.459 1 180 doce -2.047 2 106.75 mover 3.395 1 163.2 sentí -2.049 1 33.8 influjo 3.343 1 187.3 carnero -2.057 1 79.9 siembran 3.339 1 136 perseguíamos -2.072 1 109.4 algún 3.313 2 123.4 echaba -2.098 2 115.85 diferente 3.308 5 137.4 profesores -2.101 1 35.1 cama 3.307 1 158.1 otras -2.145 1 133.3 cerquita 3.305 3 140.233 vacas -2.188 1 91.9 dejan 3.293 1 174.3 podía -2.204 3 100.8 cosechaba 3.289 3 112.333 yerba -2.217 5 82.78 pregunto 3.289 1 140.4 quieren -2.24 2 90.9

259

llevando 3.269 1 152.8 adentro -2.265 1 86.9 levantaba 3.262 1 156.6 alguien -2.278 3 101.567 dejaron 3.243 1 133 costumbre -2.286 1 14.5 sacar 3.225 1 149.3 respecto -2.33 1 40.4 libertad 3.219 1 139.5 cada -2.331 4 79.1 hablan 3.213 14 118.814 margarita -2.356 1 131.7 troca 3.206 1 169.4 acabe -2.358 1 55.5 compre 3.188 1 179.5 cuesta -2.388 1 45.9 vidrio 3.169 1 135.3 comunidades -2.391 1 83.6 gustaba 3.167 2 134.7 querían -2.398 6 128.3 lugarcito 3.164 1 178.4 superintendente -2.405 1 75.6 volvían 3.164 1 191.5 queda -2.432 2 97.2 daban 3.145 4 141.85 aparecían -2.455 1 36.4 conozco 3.137 1 135.4 leer -2.455 2 128.4 plaza 3.13 1 155.6 nació -2.456 9 77.644 tío 3.119 3 124.867 amistades -2.457 1 24 mujer 3.112 2 128.05 filipina -2.48 1 28.1 tocan 3.096 1 171.7 aprendí -2.499 6 115.267 culpa 3.084 1 152.3 vivido -2.511 1 47 puros 3.077 1 174.9 velorio -2.518 1 82.6 millas 3.054 1 176.7 primeramente -2.567 1 75.7 decíamos 3.031 1 185.2 envidia -2.569 1 85 mujeres 3.027 3 129.367 quiere -2.57 8 91.175 robo 3.021 1 183 comida -2.617 3 112.5 escuchar 3.01 2 114 peligro -2.621 1 67.9 lote 3.01 1 194.1 mediación -2.627 1 8.1 decir 3.009 1 155.3 curaban -2.632 2 90.7 diferencias 2.995 1 161 tocara -2.65 1 41.7 cuidado 2.989 1 173.1 peleamos -2.662 1 62 aprendemos 2.988 1 191.3 pagamos -2.675 1 70.9 igual 2.917 1 146.3 vegas -2.679 2 108.65 mañana 2.908 2 174.05 cantar -2.705 1 4.2 comenzamos 2.899 1 161.5 compadre -2.773 1 36.5 horas 2.85 2 149.55 grano -2.775 1 60.4 divorciaron 2.822 1 131.6 pensar -2.79 1 3 lingo 2.819 1 184.2 crecía -2.809 1 38.4 después 2.815 3 98.033 llanito -2.811 1 105 pedacito 2.813 1 160.4 cuarto -2.841 2 83.45 hablo 2.797 10 128.37 yerbas -2.912 1 42.5 quebrando 2.786 1 145 cinco -2.919 9 68.356 agarraba 2.757 1 150.1 pichoncitos -2.929 1 48.6 llamo 2.753 1 178.6 metían -2.932 1 31.8 decidieron 2.752 1 169.2 trataban -2.946 1 18.7 llevaron 2.746 1 182.1 pelos -2.956 1 8.6 pura 2.742 1 137.5 música -2.957 1 78.9 rastreo 2.715 1 131.6 lenguaje -2.964 1 83.2 siempre 2.705 18 95.728 hacían -3.004 2 45.1 jabón 2.699 1 135.9 lleno -3.021 2 87.65 venirse 2.692 1 163.6 cuantos -3.056 1 11.6 siembro 2.682 1 114.3 borrega -3.067 3 92.3 barra 2.656 1 153.1 vivían -3.067 2 82.6 jara 2.626 2 98.9 echarle -3.069 1 4.3 encanta 2.62 1 151.7 televisión -3.069 2 76.85 autores 2.618 1 179.7 ahí -3.073 1 38.5 rumbo 2.615 1 173.8 clase -3.114 2 87.7 ando 2.608 1 148.1 voltean -3.134 1 32.4

260

entraba 2.58 1 160.9 meterle -3.145 1 8.9 hicistes 2.561 1 146.4 marcamos -3.163 1 9.1 aquellos 2.551 1 153.3 doctor -3.188 1 2 calabaza 2.53 1 187.3 totalmente -3.201 1 45.8 cayo 2.501 1 148 seguíamos -3.217 1 108.4 fuimos 2.495 4 123.325 dijeron -3.229 1 28.7 asociación 2.487 1 109.3 salió -3.231 1 124.2 luego 2.487 14 125.929 mojado -3.254 1 50.1 gemela 2.481 1 167.3 amiga -3.259 3 118.767 llevar 2.473 1 138.1 hallaba -3.263 3 101 gentes 2.461 1 135.3 lugar -3.268 3 92.733 todos 2.456 2 122.2 hacemos -3.276 1 13.2 sabes 2.446 1 165.8 vender -3.3 1 57.1 ahora 2.435 16 129.6 dijeron -3.33 3 65.133 maestro 2.435 1 140.1 España -3.337 1 16.6 empezaron 2.433 3 110.2 ultimo -3.357 2 106.45 hombro 2.431 1 155 hospital -3.37 1 0 semanas 2.398 1 180.4 seca -3.416 1 51.5 carpintero 2.394 1 130.1 ayer -3.419 1 82.9 once 2.391 2 158.75 siguiente -3.434 1 49.9 idioma 2.383 8 138.025 pronto -3.447 2 73 educación 2.379 1 114.9 desde -3.448 2 63.6 gustaría 2.377 1 160.6 tenían -3.46 14 114.614 anden 2.375 2 120 ustedes -3.502 1 29.3 reja 2.354 1 164.3 papas -3.519 2 86.7 escuela 2.352 15 98.027 empezó -3.527 1 12.3 ayudaba 2.324 1 163.5 salgo -3.536 1 0 corre 2.323 3 125.867 anduviera -3.545 1 27.9 esa 2.322 2 166.35 ensene -3.545 2 77.5 vergüenza 2.32 2 140.7 puerto -3.549 1 2.1 primo 2.302 1 128.3 también -3.556 18 99.983 cuidando 2.3 2 127.45 cercaron -3.558 1 22.5 poquita 2.294 2 135.1 novecientos -3.565 1 40.2 necesito 2.279 1 159.8 nacido -3.57 1 69 tanto 2.263 1 165.9 cargo -3.579 1 1.6 poquito 2.261 2 132.4 profesor -3.587 1 37.4 vide 2.24 1 167.9 sesenta -3.602 1 12.1 españoles 2.239 1 166.2 recuerdo -3.62 1 7.8 novelas 2.238 1 140.9 compro -3.672 1 20.4 doctores 2.237 1 156.6 rededor -3.719 1 39.7 esperar 2.234 1 158.7 entendía -3.723 1 99.3 anda 2.227 3 123.333 echaron -3.741 1 10 tercera 2.222 1 139.6 miraban -3.769 1 43.1 ángeles 2.204 1 148.8 control -3.773 1 5.6 decimos 2.197 4 104.95 comunicarse -3.775 1 0.7 gallo 2.181 1 162.5 cosechar -3.804 1 15.7 tirado 2.17 1 171.6 junta -3.812 1 10.6 pader 2.168 1 156.9 compraba -3.822 2 50.85 parece 2.154 1 176.6 sirve -3.843 1 0 rosarios 2.151 1 130 yerno -3.846 1 15.7 oficina 2.144 1 127.9 curiosa -3.867 1 86.1 muchacha 2.131 1 166.8 ensenaban -3.868 2 89.25 volaba 2.125 1 188.4 juntan -3.876 1 24.8 pasa 2.12 2 140 corriendo -3.886 1 47 hijo 2.117 3 164.633 cerca -3.887 2 75.25 permiso 2.109 1 187.2 pidiendo -3.904 1 14.7

261

señor 2.099 1 127 mexicano -3.933 1 12.7 gallinas 2.089 1 160.8 cuerpo -3.936 1 19.1 vive 2.085 2 154 hicieron -3.943 2 54.8 conocí 2.082 1 103.5 aprendiendo -3.952 3 71.367 remedios 2.079 3 152.1 usamos -3.987 1 24.7 pedíamos 2.077 1 170.8 dolor -3.999 2 54.1 voltear 2.066 1 138.1 crecimos -4.008 1 9.3 revistas 2.063 1 124.8 curioso -4.01 2 117.3 practique 2.06 1 153.9 dices -4.013 1 54.4 calentura 2.049 1 152.5 cuba -4.065 1 2.6 llorona 2.047 3 131.533 pueblito -4.066 2 102.9 queriendo 2.038 1 138.5 enojada -4.077 1 10.6 hablando 2.02 1 120.5 piensa -4.083 1 7.1 vivíamos 2.012 1 169.9 cierras -4.139 1 50.9 niña 1.993 2 135.95 hizo -4.143 2 101.35 impuestos 1.971 1 111.9 imagino -4.143 1 30 ales 1.964 2 137.5 generación -4.166 1 17.6 esto 1.922 1 131.9 tomado -4.18 2 78.1 encantaban 1.921 1 113.7 leyendo -4.19 2 70.8 refiere 1.902 1 134.3 ciento -4.239 1 10.1 primero 1.893 6 131.35 trajeran -4.243 1 9.5 veníamos 1.881 1 169.2 levanto -4.261 1 5.3 pastelitos 1.866 1 156.6 mucha -4.263 16 131.906 tecolotes 1.864 2 162.85 tortilla -4.273 1 21.6 una 1.852 25 123.984 aquí -4.285 14 81.221 novela 1.846 1 154.7 abuelos -4.299 2 106.8 significaba 1.823 1 119.9 haciendo -4.312 2 9.65 secundaria 1.821 1 127 cierto -4.318 1 1.6 hombre 1.82 2 130.2 valentina -4.324 1 20.1 varios 1.817 1 154 traíban -4.346 1 7.6 Pecos 1.814 1 143.9 bruja -4.358 1 55.9 suerte 1.793 1 141.5 cincuenta -4.366 7 67.086 casados 1.79 1 133.1 extraña -4.367 1 10 invierno 1.782 2 124.65 trae -4.385 1 0 mezcle 1.779 1 124.9 veces -4.397 7 127.6 aprender 1.766 1 156.1 iban -4.407 7 108.586 llamaron 1.765 1 151 traen -4.412 1 0 hicimos 1.758 1 139.9 aprendió -4.432 1 58.9 ingeniero 1.755 2 141.5 pasado -4.454 1 5.6 dieron 1.744 1 157.1 sobre -4.48 1 13 mala 1.728 1 162.6 palabra -4.483 10 101.56 bola 1.724 1 159.6 mejor -4.523 4 63.22 colorado 1.719 2 121.25 trampa -4.534 1 22.4 estoy 1.718 2 82.7 pena -4.59 1 35.4 madre 1.715 1 139.1 tuvieron -4.591 1 36.7 comemos 1.712 1 135.5 sube -4.639 1 9.2 quelites 1.7 1 167 fácil -4.666 1 16.6 hacer 1.694 2 101.2 cuidar -4.686 3 96.3 cuídense 1.69 1 153.3 estaciones -4.756 1 0 pegaba 1.678 1 139.4 levantar -4.767 1 0 Ernesto 1.671 1 126 quedara -4.769 1 24.3 peleando 1.665 1 141.9 prefiere -4.783 1 5.5 enchiladas 1.664 1 157.8 amaneció -4.784 1 0 poníamos 1.64 1 155 sociable -4.796 1 2 tapando 1.623 1 123.1 descendiente -4.802 1 12.6 trabajar 1.588 1 133.1 caro -4.824 1 13.8

262

noventa 1.572 1 147.6 estudios -4.829 1 15.2 llegando 1.568 1 128.9 caballos -4.837 1 71.9 quedo 1.532 3 133.9 casar -4.842 1 3.4 quebré 1.53 2 121 acerca -4.846 1 3.2 creció 1.503 3 135.667 quitar -4.888 1 0.003 verlos 1.501 1 140.9 santa -4.889 4 58.625 teníamos 1.495 1 152.5 agarrar -4.893 1 13.9 contento 1.487 1 122.6 cheque -4.901 1 4.4 hierba 1.485 1 157.7 hijos -4.908 3 109 nietos 1.482 2 162.75 plástico -4.922 1 8.2 chiche 1.475 1 156.7 especialmente -4.923 2 56.65 vivieron 1.469 1 126.2 chiquita -4.955 1 23.8 gordo 1.452 1 132 entienden -4.963 3 39.2 rancho 1.447 3 123.567 pueblos -4.974 1 0.8 caballo 1.42 1 134.6 jugábamos -4.98 1 1.4 amarilla 1.412 1 142 entendido -4.983 1 9.8 llamando 1.411 1 144.5 tuvo -4.994 2 44.85 éramos 1.403 1 146.3 estaban -5.002 10 90.65 mete 1.382 1 172.2 corte -5.027 1 5.5 coloniales 1.375 1 130.1 conoció -5.046 1 3.8 saber 1.363 1 157.3 llama -5.049 3 96.867 además 1.341 1 70.6 toma -5.054 1 0.5 leerlo 1.329 1 142.6 clases -5.07 1 6 trabajaban 1.329 1 117 despecharon -5.081 1 0 quedarme 1.319 1 134.6 juegos -5.081 1 0 antes 1.312 5 122.76 abajo -5.089 2 97.5 principio 1.311 1 157.5 paro -5.105 1 43.1 pasta 1.279 1 111.2 medio -5.145 5 84.42 alverjones 1.271 1 138 vivo -5.145 1 40.6 ensenar 1.27 1 133.3 pones -5.149 1 1.8 fuera 1.27 5 93.98 tradiciones -5.149 2 69.7 naturalmente 1.27 1 132.3 tripa -5.174 2 72.1 llego 1.244 5 110.46 puedes -5.182 1 11.2 acciones 1.208 1 107.6 mientras -5.192 1 14.8 hablaba 1.202 6 125 uso -5.213 1 48 llevaba 1.202 1 141.3 norte -5.225 3 71.533 agarrando 1.193 1 114.6 cuernito -5.268 1 49.4 enseno 1.177 1 166.7 navajosa -5.268 1 0.4 pasando 1.173 2 70.1 nivel -5.284 1 0 gradué 1.154 2 112.55 damos -5.29 1 0 yendo 1.153 2 106.75 coca -5.325 1 0 ayudándoles 1.151 1 119.9 tías -5.349 1 9.2 tuvieran 1.15 1 133.2 hacia -5.425 8 71.712 esfuerzo 1.145 1 131.5 acuerdo -5.458 21 62.505 dona 1.137 2 135.65 chupo -5.476 1 3 dedo 1.12 1 144.7 manzanas -5.482 1 20.1 diarrea 1.116 1 145.5 cazábamos -5.546 1 1.1 poder 1.111 1 144 pesos -5.556 1 33.5 roncar 1.102 1 74.5 canoncito -5.564 1 5.7 hierva 1.096 1 105.8 empezamos -5.627 2 64.75 conmigo 1.08 1 152.3 abuelo -5.691 4 82.9 gustara 1.07 1 128.6 cuida -5.722 1 0 telele 1.016 1 141.6 ocasiones -5.75 1 0 demás 1.015 1 130.5 interesados -5.794 1 11.4 reciente 1.005 1 101.5 brujas -5.81 4 122.925 otros 0.995 1 155.2 muchos -5.823 13 120.2

263

perdiendo 0.984 1 112.5 dormido -5.829 1 17.5 cuentos 0.981 3 89.1 venían -5.932 2 67.25 vino 0.975 3 147.6 quedas -5.939 1 1.1 nombrábamos 0.971 1 143 paraban -5.941 1 16.1 quebró 0.97 2 115.65 tengo -5.953 29 52.328 víbora 0.951 1 150.3 dure -6.016 1 12.7 cambiado 0.949 1 133 dijo -6.056 6 125.133 entrar 0.949 1 98.6 diciendo -6.063 2 6.8 uno 0.947 11 122.7 mente -6.064 1 0 mama 0.94 15 134.713 tener -6.112 2 56.15 vienen 0.939 3 124.167 pájaro -6.172 1 17.7 mudaron 0.928 1 126.8 Antón -6.187 1 0 pasaron 0.928 1 119.7 maquina -6.19 1 21.8 empanaditas 0.923 1 173.3 vena -6.192 1 10.6 ocha 0.919 2 126.75 muchacho -6.286 1 37.6 podían 0.915 3 139.8 figura -6.287 1 0.6 manera 0.909 1 157.8 noticias -6.343 1 9.5 favorita 0.908 1 168.4 roñosos -6.38 1 0 fuerzas 0.899 1 86.9 lloraba -6.437 1 14.3 hablarle 0.898 1 110.9 ibas -6.487 1 12.4 hablar 0.888 12 124.092 hombres -6.5 1 0 situación 0.881 1 92 junto -6.505 5 66.04 quedaba 0.877 2 135.85 amigos -6.507 9 105.878 quitaba 0.877 1 139.5 ponía -6.605 2 50.5 numero 0.876 1 140.2 choque -6.609 1 0 funeral 0.869 3 105.333 joven -6.66 1 1.9 piñoneros 0.866 1 124.4 cuido -6.687 3 37.967 vivimos 0.855 3 142.6 entrenados -6.706 1 25.2 digo 0.847 5 125.4 pinos -6.708 1 4.1 segundo 0.844 1 125.7 vida -6.742 5 98.94 bilingüe 0.835 1 120.9 río -6.771 1 0 aprendieron 0.834 4 133.625 tierras -6.817 1 3.4 programa 0.83 2 119.4 hubiera -6.857 1 6.1 cobra 0.805 1 85.3 ingles -6.877 8 78.662 conocía 0.797 1 93.9 tierra -6.878 5 81.18 maquinas 0.797 1 163.8 pulgadas -6.884 1 5.7 echamos 0.795 2 104.35 baño -6.969 1 3.4 preguntar 0.78 1 62.3 matas -6.984 1 17.7 arrimaba 0.772 1 132.3 iglesia -7.071 2 59.15 escribiera 0.758 1 130.3 ceniza -7.102 3 101.6 patrones 0.75 1 78.9 hijas -7.108 1 1.6 gobierno 0.743 1 129.8 ataque -7.202 1 6.7 viví 0.728 2 125.4 daba -7.278 3 90.5 ciertas 0.717 1 131 color -7.291 2 0 favoreo 0.708 1 135.2 pertenece -7.322 1 13.4 comencé 0.704 1 96.5 vivía -7.379 12 100.217 estirarlo 0.704 1 134.9 días -7.479 1 37.1 navaja 0.69 1 161 tuvimos -7.602 1 0 pueblo 0.689 1 81.5 cuarenta -7.705 6 89.267 hecho 0.678 1 152.9 comenzó -7.767 3 54.6 modo 0.663 2 128.6 puedo -7.769 5 50.34 ponerle 0.649 1 122.1 choco -8.029 2 12.6 caminaron 0.634 1 146.5 hablamos -8.07 10 114.14 ensenando 0.624 1 117 hasta -8.137 6 53.417 podrías 0.617 1 153 buena -8.249 9 102.567 baile 0.613 1 132.8 miedo -8.268 3 59.2

264

trabajamos 0.61 2 87.55 estar -8.483 3 38.3 nada 0.605 5 120.2 noches -8.536 1 0 robar 0.605 1 100.4 quisiera -8.536 2 6.4 fenómeno 0.587 1 131.4 gato -8.559 1 8.1 pudriera 0.558 1 139.4 cierra -8.611 2 6.2 humana 0.553 1 110.6 ahorita -8.629 2 72.75 severo 0.546 1 134.7 donde -8.665 4 37.075 estábamos 0.528 2 145.2 cosas -8.683 3 49 servir 0.519 1 125.2 salía -8.758 3 82.4 banda 0.508 1 113.4 pasaba -8.812 3 60.067 corrijo 0.495 1 168.6 escucho -8.905 2 14.15 problema 0.492 1 127.1 así -8.943 2 15.55 grado 0.489 1 118.4 viene -8.978 5 92.08 variamente 0.482 1 141.7 quería -9.125 10 98.19 caliente 0.475 1 128.7 platico -9.242 2 25.8 medina 0.469 1 113.7 solamente -9.439 2 29.5 venia 0.445 3 123.767 secaban -9.509 2 0 carne 0.435 5 64.46 indios -9.517 2 5.4 ponemos 0.429 1 121.6 iba -9.566 21 113.229 gustan 0.402 2 83.3 sufría -9.613 2 8.6 llamaba 0.397 7 131.871 algunas -9.743 3 69.6 pepino 0.387 2 95.8 bueno -10.267 7 83.629 comiendo 0.377 1 88.1 medicina -10.304 3 22.7 cuidaba 0.376 1 155.4 andaba -10.399 3 63.7 mariano 0.374 1 123.6 echaban -10.46 2 9.3 sembraban 0.371 1 127.3 chiquito -10.532 2 20.05 estuvo 0.36 1 134

265

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