When the Leading Tone Doesn't Lead: Musical Qualia in Context Dissertation Presented in Partial Fulfillment of the Requirements for the Degree Doctor of Philosophy in the Graduate School of The Ohio State University By Claire Arthur, B.Mus., M.A. Graduate Program in Music The Ohio State University 2016 Dissertation Committee: David Huron, Advisor David Clampitt Anna Gawboy c Copyright by Claire Arthur 2016 Abstract An empirical investigation is made of musical qualia in context. Specifically, scale-degree qualia are evaluated in relation to a local harmonic context, and rhythm qualia are evaluated in relation to a metrical context. After reviewing some of the philosophical background on qualia, and briefly reviewing some theories of musical qualia, three studies are presented. The first builds on Huron's (2006) theory of statistical or implicit learning and melodic probability as significant contributors to musical qualia. Prior statistical models of melodic expectation have focused on the distribution of pitches in melodies, or on their first-order likelihoods as predictors of melodic continuation. Since most Western music is non-monophonic, this first study investigates whether melodic probabilities are altered when the underlying harmonic accompaniment is taken into consideration. This project was carried out by building and analyzing a corpus of classical music containing harmonic analyses. Analysis of the data found that harmony was a significant predictor of scale-degree continuation. In addition, two experiments were carried out to test the perceptual effects of context on musical qualia. In the first experiment participants rated the perceived qualia of individual scale-degrees following various common four-chord progressions that each ended with a different harmony. While scale-degrees were still shown to elicit relatively stable qualia, there was a significant effect for the role of the local chord context. Importantly, this experiment was carried out using participants both with ii and without music-theoretic training, supporting the notion that the identification of scale-degrees was not responsible for the evoked qualia. This experiment also partially replicated a component of Krumhansl & Kessler's (1982) study examining the \goodness of fit” of scale-degrees within a key. However, the authors' claim that scale-degrees 1, 3, and 5 were best “fitting” due to the tonal stability of the tonic triad could not be fully supported here. In fact, the results from the present study found that the \goodness of fit” effect could perhaps be better explained by other factors. In the second experiment participants rated the perceived qualia of either com- posed inter-onset patterns or recorded song clips presented in different metrical con- texts. Both inter-onset interval pattern and meter were shown to be significant in- fluences on judgments of qualia. In addition, syncopation was found to be a strong predictor for certain components of qualia. The overall results from these studies show that musical context is an important contributor to musical qualia, and therefore, while isolated musical events may still be capable of creating relatively \stable" qualia, in real musical contexts these may change dramatically. iii Acknowledgments I would first and foremost like to thank my advisor, David Huron, for his con- tinuous guidance and support, and for his infectious curiosity and excitement for all things musical. I would also like to thank my fellow CSML colleagues, both past and present, for their feedback, advice, and camaraderie. In addition, many thanks are due to the other members of my committee, Anna Gawboy and David Clampitt, for their insights and encouragement throughout my time at Ohio State. I would also like to acknowledge the support of the Social Sciences Humanities Research Council of Canada, whose funding made possible my final year of study. Finally, I especially need to thank my \better half", Nat Condit-Schultz, for all of his help with statis- tics and programming, for his unfailing optimism, and above all, for inspiring me to become a better scholar and musician. iv Vita 2015{2016 . Graduate Research Assistant, Ohio State University School of Music 2012-2014 . Graduate Teaching Associate, Ohio State University School of Music 2008{2012 . Private Piano and Music Theory In- structor 2008 . .M.A., Music Theory, University of British Columbia 2004 . .B.Mus., Music Theory and History, University of Toronto Publications Research Publications Arthur, C., & Huron, D. (2016). The direct octaves rule: Testing a scene analysis interpretation. Musicae Scientiae. Advance online publication. doi: 10.1177/1029864915623093 Devaney, J., Arthur, C., Condit-Schultz, N., & Nisula, K. (2015). Theme and Vari- ations Encodings with Roman Numerals (TAVERN): A new data set for symbolic music analysis. In M. Muller & F. Wiering (Eds.), Proceedings of the International Society of Music Information Retrieval (ISMIR) Conference. Malaga, Spain: 728{ 734. Arthur, C. (2014). Does harmony affect scale-degree qualia?: A corpus study in- vestigating the relation of scale-degree and harmonic support. In M.K. Song (Ed.), Proceedings of the 13th International Conference for Music Perception and Cognition. Seoul, Korea: Yonsei University, 194{196. v Fields of Study Major Field: Music Area of Specialization: Music Theory vi Table of Contents Page Abstract . ii Acknowledgments . iv Vita.........................................v List of Tables . .x List of Figures . xi 1. Introduction . .1 2. On the Philosophy and Science of Musical Qualia . .4 2.1 What Are Qualia? . .4 2.2 The Problem Music Raises for the Study of Qualia (and Vice-Versa)6 2.3 Conceptual Knowledge and Qualia . .9 2.4 Qualia as Synthesis of Sensory and Cognitive Processing . 12 2.5 Introspection, Observation, and Converging Evidence . 13 2.6 Why Study Musical Qualia? . 14 2.7 Theories of Musical Qualia . 16 2.7.1 Scale-degree Qualia and Implicit Learning . 17 2.7.2 Rhythm Qualia . 21 2.8 Chapter Summary . 23 3. A Corpus Study . 26 3.1 The Corpus Analysis . 29 3.1.1 Overview . 29 3.1.2 Sampling . 30 vii 3.1.3 Methodology . 33 3.2 Evaluating the Models . 41 3.2.1 Global Hypothesis Test . 41 3.3 Descriptive Statistics . 44 3.3.1 Mode Classification . 44 3.3.2 Zeroth-order Probabilities . 46 3.3.3 First-order Probabilities . 49 3.3.4 Change in Melodic Probabilities when Harmony is Considered 52 3.4 Conclusions . 58 3.5 Discussion . 61 4. A Perceptual Study of Scale-degree in Context . 63 4.1 Introduction . 63 4.2 Method . 66 4.2.1 Participants . 69 4.2.2 Stimuli . 70 4.2.3 Procedure . 72 4.3 Results . 75 4.4 Discussion . 93 5. Rhythm Qualia . 96 5.1 Introduction . 96 5.1.1 Background . 100 5.2 A Perceptual Study: Rhythm in Context . 101 5.2.1 Introduction . 101 5.2.2 Method . 107 5.2.3 Results and Discussion . 110 5.2.4 Post-hoc Exploration of Rhythm Qualia . 120 5.3 Chapter Summary . 128 6. General Summary . 131 6.1 Recapitulation . 131 6.2 Discussion . 133 6.3 Implications for Music Pedagogy . 135 6.4 Areas for Future Research on Musical Qualia . 139 Works Cited . 141 viii Appendices 150 A. The Corpus Data . 150 ix List of Tables Table Page 3.1 Illustration of Encoding Key Changes . 38 3.2 Melody and Harmony Encodings at Key Changes . 40 4.1 Result Statistics by Dependent Variable . 76 4.2 Tally of \Opt-outs" by Dependent Variable . 77 4.3 Correlations with the K&K Profile . 89 5.1 Similarity Measures Between Dependent Variables . 114 5.2 Syncopation Scores for Rhythm Stimuli . 123 x List of Figures Figure Page 2.1 Example of Identical Acoustic Information Generating Unique Qualia 17 2.2 Flow Chart of Diatonic Scale-degree Probabilities from Huron (2006) 18 3.1 Zeroth-order Distribution of Scale-degrees in the Corpus . 47 3.2 Zeroth-order Distribution of Harmonies in the Corpus . 48 3.3 First-order Probabilities for Scale-degrees . 50 3.4 Predicted and Observed Probabilities for 1^ in Tonic Context . 53 3.5 Effect of Harmony on Scale-degree Probability (continued on next page) 55 4.1 Image of Digital Interface Used in Experiment . 73 4.2 Scale-degree Qualia Ratings (continued on next page) . 80 4.3 Consistency Between and Across Participants . 84 4.4 Intra-Subject Correlations . 86 4.5 Key Profiles from Krumhansl & Kessler (1982) . 87 4.6 Present Data Compared to Krumhansl & Kessler's (1982) Key Profiles 88 5.1 Three Identical Onset Patterns in Different Metrical Contexts . 99 5.2 Rhythm Stimuli (Composed) . 105 xi 5.3 Rhythm Stimuli (Borrowed) . 107 5.4 List of Rhythmic Descriptor Terms . 109 5.5 Rhythm Qualia Ratings - Composed Rhythms (continued on next page)111 5.6 Rhythm Qualia Ratings - Song Clips . 117 5.7 Amount of Syncopation and \Grooviness" . 124 5.8 Additional Examples of Syncopation Predicting Qualia . 125 xii Chapter 1: Introduction This dissertation examines whether certain fundamental components of musical structure, such as scale-degree and rhythm, can generate unique, qualitative musical experiences, or \qualia," and in particular whether the musical context | in this case harmony and meter, respectively | can affect those experiences. Chapter 2 introduces the topic of qualia, briefly mentions its philosophical origins, and discusses its role in music. In particular, the concepts of scale-degree and rhythm pose a challenge to many traditional accounts of what constitutes \qualia" on account of their being referential. In addition, many philosophers who claim qualia to be ineffable pose a challenge to empirical researchers wishing to study musical qualia. This chapter also reviews the literature on music and qualia, and summarizes theories about the generation of musical qualia, giving special attention to the role of implicit learning. It then proposes an operational definition of qualia, similar to those used by Zentner (2012) and Dowling (2010), that supports a perspective conducive to the evaluation of qualia as an object for scientific study.