Prevalence of Vowel-Initiated Words in the Core Vocabulary of 100 Languages
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投稿類別﹕英文寫作類 篇名﹕ Prevalence of Vowel-initiated Words in the Core Vocabulary of 100 Languages 作者﹕ 趙子甯。國立台南女子高中。高一 4 班 指導老師﹕ 林永芬老師 Prevalence of Vowel-Initiated Words in 100 Languages I. Foreword “Where there is shouting, there is no true knowledge.” (Leonardo da Vinci, n.d.) These words strike a chord with the truth if it is talking about how to take care of our voice. We believe shouting is bad for our voice not only because our doctors or voice teachers have warned us against it, but also because some of us have actually experienced losing our voice or having a croaky voice after shouting in a sports event. Specifically, bursting out voiced segments with excessive force can damage our vocal fold tissues and make us sound harsh. To promote the awareness of this counterproductive voicing behaviour, it is important to learn where and how often it can occur in a language. Therefore, this study aims to assess the occurrence rate of words where speakers may be at risk of using a “shouting” mode. II. Thesis This thesis starts by explaining why forceful vocal behaviour can occur in vowel-initiated words and cause voice problems. A section then follows to link this voice problem with language by addressing the speculation that some language speakers may sound harsher due to a higher occurrence rate of vowel-initiated words. Following a description of the research question and rationale for comparing this feature across languages are the method, result, and discussion sections. Vowels and Voicing All spoken languages consist of vowels and consonants as their building blocks. Vowels differ from consonants in that exhaled air flows through the mouth freely in the former but encounters constricted areas in the latter (Titze, 1994). Both vowels (e.g., /i/, /u/) and voiced consonants (e.g., /b/, /z/) require vocal fold vibration, but vowels are normally longer than consonants and thus may have a more substantial impact on vocal folds during vocal fold vibration. According to the myoelastic-aerodynamic theory of phonation (Titze, 1994), vocal fold vibration involves bringing vocal folds closer together at the start of voicing. This narrowing of the space between vocal folds triggers a Bernoulli sucking effect, which then brings them even closer. While vocal folds block the airflow, air pressure below the closed vocal folds starts to build up until it is strong enough to push open the vocal folds. Once the vocal folds are blown apart, it will spring back toward the midline again and start another cycle of opening and closing. However, the way a speaker closes vocal folds at voice onset can differentially affect this vibration. Hard Glottal Attack Depending on whether vocal folds are loosely or tightly brought together, voice initiation can be classified as a hard, normal, or soft glottal attack (Moore, 1938; Behrman, 2007). Hard glottal attack (HGA) is a forceful vocal behaviour where vocal folds are slammed together and abruptly 1 Prevalence of Vowel-Initiated Words in 100 Languages opened (Behrman, 2007). Voice produced with a HGA is characterized by a sudden pitch and loudness change at voice onset (Orlikoff and Kahane, 1996; Shrivastav, 1999). Physiological measures have associated HGA with a faster time in the build-up of air pressure to blow open the vocal folds (Watson et al., 2016). Research has found voice patients to exhibit more HGAs than individuals with healthy voice (Andrade et al., 2000). To eliminate voice problems caused by tension in and around the throat, HGA is often targeted in vowel-initiated words and replaced with a soft attack (Boone et al., 2005). Voice and Language As vowel-initiated words present a risk for hard glottal attack, speakers of a language loaded with vowel-initiated words may sound harsher than those of other languages. This does not mean, however, that the former will necessarily show a higher rate of voice problems. The reason is that there are a myriad of factors that can adversely affect voice. Some examples are smoking, dehydration, prolonged voice use, and use of inappropriate pitch or poor respiratory support during speaking (Boone et al., 2005). The prevalence of voice disorders varies by age, profession, and other factors (Mathieson, 2001). Although it is hard to establish a link between the prevalence of voice problems and a specific language feature, it is worthwhile to investigate the prevalence of utterances predisposed to harmful vocal behaviours and compare it across languages to identify those who may be at risk. Language Classification. The number of languages spoken today has been estimated at up to 10,000 (Crystal, 1987, p. 284). To date, there are at least 7,097 languages being spoken in the world according to Ethnologue, an authoritative language database updated annually by a US- based linguistic society (SIL International, n.d.). These languages have been grouped into 152 language families (SIL International, n.d.). Crystal (1987) has described three common language grouping methods: genetic, typological, and areal classifications (p. 293). While genetic and areal classifications focus on historical lineage (p. 293) and geographical proximity (p. 24), the typological approach is based on a comparative analysis that makes no assumption about the historical or regional connections (p. 293). Despite the complexity of categorization process, the classification of languages into families provides a useful basis for language comparison. As far as language families are concerned, the local languages used in Taiwan fall into two language families: Sino-Tibetan and Austronesian. The majority of people in Taiwan speak Mandarin as well as Taiwanese, called “Tai-gi” or “Taiwanese” by its native speakers (Liao, 2008). Ethnology (SIL International, n.d.) labels Taiwanese as “Min” and classifies both Mandarin and “Min” as subgroups of Sino-Tibetan. The largest aboriginal group in Taiwan is the Amis, followed by Paiwan (Demographics of Taiwan, n.d.). The native languages of these two aboriginal groups have both been classified as Austronesian (Formosan languages, n.d.) These languages are included in this study, along with other world languages, to allow for a comparison within Taiwan and globally. 2 Prevalence of Vowel-Initiated Words in 100 Languages Research Question and Importance The main research question is: Is there a language difference on the prevalence of vowel- initiated words? If so, how are different language families differ? Can it help explain why speakers of a certain language may sound harsher than those of other languages and thus demystify the stereotype? Can the difference be used to explain about the variability of the prevalence of voice problems? These are important questions because speakers of a language full of vowel-initiated words can benefit from being aware of the importance of using easy voice onset. Materials and Methods Word List. To facilitate a cross-language comparison, this study employs the Swadesh list in English as the basis to generate an equivalent list in the Roman transcriptions of another language. The Swadesh list, which is a list of 207 words identified as the core vocabulary of any language, has been widely used to compare languages and find traces of historical lineage (Swadesh List, n.d.). Appendix 1 shows a Swadesh list of the English words, along with their corresponding Mandarin, Taiwanese, Amis, and Piwan words in Roman transcription. Selection Criteria. In addition to the five languages mentioned above, languages with Roman transcriptions available in the Google Translate website are all included. Instrument. A computer equipped with Excel and Internet access was used to perform language translation, internet search, data analysis, and graphing. The online tools used include Google Translate, Taiwanese Aboriginal Online Dictionary (Council of Indigenous People, 2017), and Taiwanese Online Dictionary (Taiwanese Ministry of Education, 2011). Procedures. To generate the Roman transcriptions for each language, the 207 words of the Swadesh list are copied onto Google Translate, with input and output languages specified. For Taiwanese, Amis, and Paiwan, which are not available on Google Translation, the Mandarin words were copied one by one onto the two language-specific online dictionary sites as mentioned previously to obtain the Roman transcriptions for these two languages respectively. The generated words were copied onto Excel and sorted into alphabetical order. In Excel, the “countif” function was used to tabulate the number of words starting with /a, e, i, o, u/ and vowels with letters with diacritical marks (e.g. umlaut). The percentage of vowel-initiated words was then calculated using the arithmetic function in Excel for each and every one of the languages. Results Language Included. This study includes a total of 100 languages, which come from a total of 16 language families (Table 1). As shown in Table 1, the largest language family included in this study is Indo-European, whose seven subgroups are included in this study. The largest Indo- European subgroup included in this study is Balto-Slavic (13 languages), followed by Germanic (11 languages), Italic (9 languages) and Indo-Iranian (9 languages), Celtic (3 languages), Albanian (1 language), Armenian (1 language), and Helena (1 language). 3 Prevalence of Vowel-Initiated Words in 100 Languages The other language families included are Austronesian (11 languages), Niger-Congo (8 languages), Afro-Asiatic (6 languages), Turkic (5 languages), Dravidian (4 languages), Sino- Tibetan (3 languages), Uralic (3 languages), Tai-Kadai (2 languages), Austroasiatic (2 languages), Kartvelian (1 language), Koreanic (1 language), Japonic (1 language), Mongolic (1 language), French Creole (1 language), Hmong-Mien (1 language), Language Isolate (1 language), and Esperando (1 language). Prevalence of Vowel-Initiated Words. Table 1 lists the prevalence of vowel-initiated words in the core vocabulary of these languages, along with their respective language family. As shown in Table 1, the prevalence of vowel-initiated words ranges from 0 (Thai) to 63.29 (Zulu), with a mean of 15.25% (SD = 10.32).