Arts, Faculty of
Music, School of
DSpace
UBCV
Lee, Yin Hei (Jason)
Master of Arts - MA
University of British Columbia
Cantonese is a tone language, meaning that differences in pitch can contribute to different word meanings. In songs written in a tone language, song melody and linguistic tones should ideally correlate with each other, in order to maintain intelligibility of the lyrics. The topic of tone-melody correspondence has been examined by music and language scholars in many cultures and genres, including Cantonese popular music (hereafter Cantopop). However, previous scholars who examined the topic of tone-melody correspondence in Cantopop have not supported their arguments with evidence from a large and representative sample. In many cases, researchers only looked at select passages in songs, but without following a rigorous methodology for selecting the passages or even the songs themselves. As a result, their findings are partial and might not accurately describe how Cantopop lyrics are written to ensure the intelligibility of the tones and the syllables. In this study, I construct a 105-song Cantopop corpus. This sample size is much larger than those used in previous studies, and the selection criteria for the songs are clearly defined to ensure representativeness. Using data from this corpus, I revisit claims and observations made in previous research on tone-melody correspondence in Cantopop. In Chapter 4, I challenge and supplement the endpoint principle, a widespread assumption in the study of tone-melody correspondence in Cantopop regarding the text-setting treatment for syllables with contour tones. In Chapter 5, I propose a refined way of describing the text-setting constraint for Cantopop in relation to the two types of oblique motion between speech and song melodies. In addition, to explain the opposite directionality of oblique II bigrams, I explore the role of pitch range in Cantopop text-setting, which was overlooked in previous studies. This study contributes to the study of Cantopop and tone-melody correspondence by offering a large and representative corpus of the genre and providing new insights about observations that have been previously overlooked.
A CORPUS STUDY OF TONE-MELODY CORRESPONDENCE IN CANTOPOP, 2000–2020 by Yin Hei Lee (Jason) B.A., The Chinese University of Hong Kong, 2021 B.Sc., The Chinese University of Hong Kong, 2018 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF ARTS in The Faculty of Graduate and Postdoctoral Studies (Music, Emphasis Theory) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) April 2023 © Yin Hei Lee (Jason), 2023 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: A Corpus Study of Tone-Melody Correspondence in Cantopop, 2000–2020 submitted by Yin Hei Lee (Jason) in partial fulfilment of the requirements for the degree of Master of Arts in Music, Emphasis Theory Examining Committee: Leigh VanHandel, Associate Professor, Music Theory, UBC Co-supervisor Hedy Law, Associate Professor, Musicology, UBC Co-supervisor iii Abstract Cantonese is a tone language, meaning that differences in pitch can contribute to different word meanings. In songs written in a tone language, song melody and linguistic tones should ideally correlate with each other, in order to maintain intelligibility of the lyrics. The topic of tone-melody correspondence has been examined by music and language scholars in many cultures and genres, including Cantonese popular music (hereafter Cantopop). However, previous scholars who examined the topic of tone-melody correspondence in Cantopop have not supported their arguments with evidence from a large and representative sample. In many cases, researchers only looked at select passages in songs, but without following a rigorous methodology for selecting the passages or even the songs themselves. As a result, their findings are partial and might not accurately describe how Cantopop lyrics are written to ensure the intelligibility of the tones and the syllables. In this study, I construct a 105-song Cantopop corpus. This sample size is much larger than those used in previous studies, and the selection criteria for the songs are clearly defined to ensure representativeness. Using data from this corpus, I revisit claims and observations made in previous research on tone-melody correspondence in Cantopop. In Chapter 4, I challenge and supplement the endpoint principle, a widespread assumption in the study of tone-melody correspondence in Cantopop regarding the text-setting treatment for syllables with contour tones. In Chapter 5, I propose a refined way of describing the text-setting constraint for Cantopop in relation to the two types of oblique motion between speech and song melodies. In addition, to explain the opposite directionality of oblique II bigrams, I explore the role of pitch range in Cantopop text-setting, which was overlooked in previous studies. This study contributes to the study of Cantopop and tone-melody correspondence by offering a large and representative corpus of the genre and providing new insights about observations that have been previously overlooked. iv Lay Summary In this study, I construct a 105-song corpus of Cantonese popular music for studying the interaction between linguistic tones and song melody in the genre. This sample size is much larger than those used in previous studies, and the selection criteria for the songs are clearly defined to ensure representativeness. This addresses the methodological shortcoming in many earlier studies. Using data from this corpus, I revisit claims made in previous research on tone-melody correspondence in Cantopop. I challenge and refine assumptions made by earlier scholars and offer new perspective as to how one should understand the text-setting constraint for Cantopop text-setting. This study contributes to the study of Cantopop and tone-melody correspondence by offering a large and representative corpus of the genre and providing new insights about observations that have been previously overlooked. v Preface This thesis is original and independent work by the author, Yin Hei Lee (Jason). A general overview of this study, as well as some preliminary data, was presented under the same title at the 2022 Joint Meeting of the American Musicological Society (AMS), Society for Ethnomusicology (SEM), and Society for Music Theory (SMT) during the meeting of the SMT Music Informatics Interest Group meeting (November 11, 2022). Otherwise, this work has not been previously published. vi Table of Contents Abstract ........................................................................................................................................ iii Lay Summary .............................................................................................................................. iv Preface ........................................................................................................................................... v Table of Contents ...................................................................................................................... vi List of Tables ........................................................................................................................... viii List of Figures ............................................................................................................................. ix Glossary ....................................................................................................................................... xi Acknowledgements ................................................................................................................. xiii 1. Introduction ........................................................................................................................... 1 2. Overview of Cantonese Tones and Tone-Melody Correspondence .......................... 3 2.1. Cantonese tones .......................................................................................................................... 3 2.2. The idea of tone-melody correspondence ............................................................................... 7 2.3. Tone-melody correspondence in Cantonese—A historical and methodological overview ................................................................................................................................................. 12 3. Methodology ....................................................................................................................... 15 3.1. Research objectives and questions ......................................................................................... 15 3.2. Construction of corpus ............................................................................................................. 17 3.3. Issues of representation in the corpus ................................................................................... 23 3.4. Data transcription and related issues .................................................................................... 25 vii 4. The Problem of Contour Tones ....................................................................................... 36 4.1. Contour tones and the endpoint principle ............................................................................ 36 4.2. Evaluating the endpoint principle ......................................................................................... 38 4.3. Evidence from the Cantopop corpus ..................................................................................... 44 4.3.1. Data on high-register tones (level T1 [55] and contour T2 [25]) ................................ 44 4.3.2. Data on mid-register tones (level T3 [33] and contour T5 [23]) ................................. 47 4.4. Discussion .................................................................................................................................. 49 5. Theoretical Issues about Oblique Motion .................................................................... 59 5.1. The frequency of oblique I vs. oblique II motion ................................................................. 59 5.2. Pitch range and directionality of oblique II motion ............................................................ 69 5.2.1. Evidence on the opposite directionality and its explanations ................................... 70 5.2.2. Evidence related to pitch range in Cantopop text-setting .......................................... 73 5.2.3. Considering the range factor and the direction factor ................................................ 80 6. Conclusion ........................................................................................................................... 84 Bibliography ............................................................................................................................... 88 Appendices ................................................................................................................................. 97 Appendix A: List of the 105 Cantopop songs included in the corpus .......................................... 97 Appendix B: Count of bigram types with all combinations of speech melodies and song melodies ............................................................................................................................................... 102 viii List of Tables Table 1. Different numbering systems for the six Cantonese tones .................................................... 4 Table 2. Generalization about contour and tonal target of the six Cantonese tones ........................ 6 Table 3. Summary of contrapuntal relationship between speech and song melodies ................... 10 Table 4. Bigrams in the first line from “活着 (wut6 zoek6) Viva” ..................................................... 10 Table 5. Analysis-based studies and number of Cantopop examples examined ............................ 13 Table 6. The four major media outlets and their song awards (Chu 2017) ...................................... 18 Table 7. Breakdown of the Preliminary Set by year and number of awards each song receives . 21 Table 8. Count of bigrams with T3 [33] and T5 [23], adapted from Ladd (forthcoming, Table 4) 42 Table 9. Count of each bigram type with high-register tones ............................................................ 44 Table 10. Count of each bigram type with mid-register tones ........................................................... 47 Table 11. Frequency distribution of the six Cantonese tones in Cantonese speech and Cantopop corpora ....................................................................................................................................................... 52 Table 12. Proportion of contrapuntal motions in previous quantitative studies on Cantopop .... 60 Table 13. Proportion of contrapuntal motions in my Cantopop corpus .......................................... 62 Table 14. Proportion of contrapuntal motions in my Cantopop corpus with row totals ............... 67 Table 15. Odds ratios for direction of song melodies as predicted by distance from pitch extremes ..................................................................................................................................................... 78 Table 16. Odds ratios for T1–T1 and T4–T4 bigrams as predicted by distance from pitch extremes ..................................................................................................................................................... 79 Table 17. Odds ratios for T1–T1 and T4–T4 bigrams as predicted by distance from pitch extremes, after controlling for the direction of the song melody ...................................................... 83 ix List of Figures Figure 1. Speech melody of the first line from “活着(wut6 zoek6) Viva” .......................................... 8 Figure 2. Transcription of the first line from “活着(wut6 zoek6) Viva” ............................................. 9 Figure 3. Distribution of awarded songs among the four channels in the Preliminary Set .......... 20 Figure 4. Distribution of lyricists in the corpus .................................................................................... 24 Figure 5. Distribution of singers in the corpus ..................................................................................... 24 Figure 6. First 22 lines of Humdrum representation of “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102) ........................................................................................................................................................ 25 Figure 7. Lyrics of the first prechorus in “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102) with Jyutping ...................................................................................................................................................... 29 Figure 8. An excerpt of the first prechorus of “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102), including phrasing and Jyutping ........................................................................................................... 30 Figure 9. An excerpt from the last chorus of “七友 (cat1 jau5)” (C0301) .......................................... 33 Figure 10. An excerpt from the second chorus of “重新長大 (cung4 san1 zoeng2 daai6)” (C1205) ..................................................................................................................................................................... 33 Figure 11. An excerpt from the first chorus of “無賴 (mou4 lai2)” (C0505) ..................................... 34 Figure 12. Decision tree for selecting mapping locus within a melisma .......................................... 35 Figure 13. Bigrams with level and contour tones ................................................................................. 36 Figure 14. An excerpt of “落花流水 (lok6 faa1 lau4 seoi2)” reproduced from Ho (2006, fig. 10) . 39 Figure 15. An excerpt of “數你 (sou2 nei5)” adapted from Ho (2010, ex. 4-14) ............................... 40 Figure 16. Distribution of song melody for T1–T1 [55] bigrams ........................................................ 45 Figure 17. Distribution of song melody for bigrams with a pair of high-register tones ................ 46 Figure 18. Distribution of song melody for T3 [33]–T3 [33] bigrams ................................................ 48 Figure 19. Distribution of song melody for bigrams with a pair of mid-register tones ................. 49 Figure 20. Vocal pitch contour of the first eight syllables in “世上只有 (sai3 soeng6 zi2 jau5)” (C0405) ........................................................................................................................................................ 51 Figure 21. An excerpt from the first verse of “烈女 (lit6 neoi2)” (C0504) ......................................... 53 x Figure 22. An excerpt from the second verse of “烈女 (lit6 neoi2)” (C0504) ................................... 54 Figure 23. Distribution of speech melody for bigrams with a descending major second .............. 55 Figure 24. An excerpt from the final chorus of “我們都是這樣長大的 (ngo5 mun4 dou1 si6 ze2 jeong6 zoeng2 daai6 dik1)” (C1502) ....................................................................................................... 56 Figure 25. Vocal pitch contour of an excerpt from the final chorus of “我們都是這樣長大的 (ngo5 mun4 dou1 si6 ze2 jeong6 zoeng2 daai6 dik1)” (C1502) ..................................................................... 56 Figure 26. Distribution of interval sizes in the Cantopop corpus ...................................................... 63 Figure 27. The distribution of melodic intervals in the Rolling Stone corpus (reproduced from Temperley .................................................................................................................................................. 65 Figure 28. Text-setting constraints for level vs. moving song melodies ........................................... 68 Figure 29. Distribution of bigram types given a song melody in a certain direction ..................... 71 Figure 30. Three-way association relating to the opposite directionality for T1–T1 and T4–T4 bigrams ....................................................................................................................................................... 74 Figure 31. An excerpt from the first prechorus of “明年今日 (ming4 nin4 gam1 jat6)” (C0205) .. 75 Figure 32. Distribution of pitch range in the corpus ........................................................................... 76 Figure 33. Distribution of song melody based on distance from pitch extremes ............................ 77 Figure 34. Distribution of bigram types based on distance from the pitch extremes ..................... 79 Figure 35. Distribution of bigram types with downward song melodies based on distance from the pitch extremes ..................................................................................................................................... 81 Figure 36. Distribution of bigram types with upward song melodies based on distance from the pitch extremes ........................................................................................................................................... 82 xi Glossary Aria types (梆黃): One of the major sung components in Cantonese Opera. One of the aria types were studied by Bell Yung (1983) as the first scholarly attempt to understand tone-melody correspondence in Cantonese music. Bigram: A pair of consecutive syllables and their respective accompanying pitches in a song. Chao number: A set of numbers ranging from 1 to 5, which linguists use to describe the pitch height of a tone. The lowest pitch is represented by “1” and the highest by “5” (Chao 1930). Contour tone: The type of tone in which the pitch height changes within a syllable. Contrary motion: The case where the speech melody and the song melody proceed in opposite directions (i.e., one goes up and the other goes down). Endpoint principle: The assumption that a syllable with a contour tone should be set in the same manner as a syllable with a level tone that has the same tonal target the contour tone. Entering tone (入聲): A type of tone in Cantonese which describes syllables ending with unreleased plosive consonants (-p, -t, and -k). Level tone: The type of tone in which the pitch height remains the same throughout a syllable. Linguistic tone (or simply “tone”): Pitch contrasts that distinguish between word meanings in a tone language. Mapping locus: The pitch with the greatest structural importance in the song melody within a melismatic syllable. This pitch serves to form bigrams with neighbouring syllables. Melodic regression: A cross-cultural phenomenon where pitches in a melody tend to return to the middle of the range after approaching the pitch extremes. Music-first, word-later (先曲後詞): The songwriting process for Cantopop in which the song melody is first written by composer and a lyricist would then compose the text for the given melody. xii Oblique motion: The case where one of the speech melody and the song melody moves upward or downward while the other stays level. Oblique I motion: A subcategory of oblique motion where the speech melody moves upward or downward while the song melody stays level. Oblique II motion: A subcategory of oblique motion where the song melody moves upward or downward while the speech melody stays level. Similar motion: The case where the speech melody and the song melody move in the same direction (downward, upward, or level). Song melody: The sequence of melodic pitches in the vocal melody. In a bigram, the song melody refers to the melodic interval between the two pitches. Speech melody: The sequence of pitch heights constituted by tones of syllables in a bigram. Text-setting constraint: The requirement for lyricists or songwriters of songs in a tone language to ensure tone-melody correspondence. Tonal onset: The starting pitch height of a tone. Tonal target: The ending pitch height of a tone. Tone-melody correspondence: The tendency for linguistic tones and song melody to correlate with each other so that lyrics in a tone language can be intelligible. xiii Acknowledgements I am deeply grateful to Dr. Leigh VanHandel and Dr. Hedy Law for their unwavering support and confidence throughout the course of this project. Their insightful feedback has been indispensable to my growth as a writer, scholar, and person. I would like to thank Dr. John Roeder, Dr. Ève Poudrier, and other faculty members at the School of Music for their guidance and encouragement during my studies at UBC. My gratitude extends to my family and friends, who have been nothing but understanding and caring all these years. 1 1. Introduction Approximately half of the world’s languages are tone languages (Hyman 2011, 198),1 but music in tone languages has not received proportionate scholarly attention. There has been much research on the musical abilities of speakers of tone languages (Jäncke 2012; Deutsch 2019, 88–94; Temperley 2022), whereas music in tone languages remains little explored. A tone language is a language in which “differences in pitch are used to distinguish lexical or grammatical meaning” (Kirby 2021, 291),2 and the contrasting pitches constitute what linguists call linguistic tones. Since different linguistic tones can indicate contrasts in word meaning, words could become unintelligible or misunderstood when said in a wrong pitch. Therefore, in songs written in a tone language, songwriters and lyricists produce songs within a “text-setting constraint” (Ladd and Kirby 2020), meaning that song melody and linguistic tones should ideally correlate with each other, in order to maintain intelligibility of the lyrics. Hence, the topic of tone-melody correspondence has been examined by music and language scholars in many cultures and genres, including Cantonese popular music (hereafter Cantopop). However, when it comes to the empirical data of tone-melody correspondence as reported in published scholarship on Cantopop, the sample sizes are usually small, and the representativeness of the song samples is often not sufficiently justified. In many cases (e.g., M. K. M. Chan [1987], Ho [2010], and Chow [2012]), researchers only looked at select passages in songs, but without following a rigorous methodology for selecting the passages or even the songs themselves. Therefore, as they drew conclusions about specific musical and linguistic properties of specific passages, they also failed to place these properties in the broader context 1 Some researchers have used the term “tonal language” instead of “tone language” (Yung 1983; Chen-Hafteck 1999; Lau and James 2004). 2 Difference in lexical meaning refers to the difference between definitions of words as put down in a dictionary, such as the difference between “run” and “rum”. Grammatical contrast exists between words with the same lexical meaning but with differences regarding grammatical categories such as tense, case, and number—for example, the difference between “run” and “ran”. 2 of the entire song or the Cantopop genre during a given period of time. In other words, the findings in these studies are often partial. Corpus studies offer precisely a rigorous methodology for addressing the problem of using small and unrepresentative samples. Musical corpus research—broadly defined as “research with large bodies of music” (Marsden 2022)—originated in 1927 and has proliferated since the turn of the century (Temperley and VanHandel 2013). This methodology has not been used at scale for studies of Cantopop. Thanks to the advancement of computer programming technology—such as the development of MusicXML, MEI, and Humdrum formats for representing musical data (see Huron [2013] and Devaney and Gauvin [2019])—researchers can now analyze much larger samples of music efficiently. In recent years, corpus studies have led to discoveries in many topics of music research, including those related to language-music relationship (e.g., Temperley [2017], Tan et al. [2019], and X. Zhang and Cross [2021]). However, to date, no published study has introduced a representative corpus of Cantopop. By “representative” I mean a corpus constructed with well-defined selection criteria that capture the most visible and recognized songs in the given period of time. By analyzing data from a substantial 105-song corpus that is representative of the genre, I plan to revisit claims and observations made in previous research on tone-melody correspondence in Cantopop. More importantly, through this research I will incorporate terminologies and methodologies from latest linguistic and music research in the study of Cantopop, which currently lacks consistency in terminology and overlooks some latest methodologies. By doing so, I wish to provide an updated and consolidated groundwork for the further study of Cantopop. 3 2. Overview of Cantonese Tones and Tone-Melody Correspondence 2.1. Cantonese tones Cantonese is a tone language belonging to the Sino-Tibetan language family, under the Chinese branch (Eberhard, Simons, and Fennig 2022).3 There are two systems to categorize Cantonese tones: a six-tone and a nine-tone system. The six-tone system is more widely accepted among modern linguists, whereas the nine-tone system is an outdated model no longer adequate for describing modern Cantonese phonology (Cheung 2016). The six-tone categorization is based on the fundamental frequency (F0) of each tone, meaning that tones are categorized according to the perceived pitch shape and height while a syllable is being spoken. It is notable that although pitch is not the unique aspect of linguistic tones (Wee 2019, 15–16), Cantonese speakers take the F0 profile of the words as the primary cue for tone identification (Flynn 2001, 14; Khouw and Ciocca 2007, 105). Each of the six tones are thus characterized by pitch register (high, mid, low, extra-low) and pitch contour (level, rising, falling). To systematically represent each tone’s pitch profile as described by pitch register and contour, most linguists of Cantonese have adopted the five-level numbering system pioneered by Yuen Ren Chao (1930). In this system, “5” stands for the highest pitch height and “1” the lowest, though differences between these pitch heights are relative and approximate, not absolute and precise. Linguists typically call these numbers “Chao numbers” when describing pitch profiles of Cantonese tones (Schellenberg 2013; Kirby, forthcoming; Ladd, forthcoming). Unlike some other tone languages such as Mandarin and Vietnamese, in Cantonese there are no tones with complex contours (i.e., dipping or peaking contours with turning point[s]). Therefore, Chao numbers can represent pitch profile of each Cantonese tone by only two numbers, representing the initial and ending pitch heights respectively. These two pitch 3 Whether Cantonese is a Chinese dialect or a separate language is an age-old topic for debate. See Cheng and Tang (2016, 18–20) for a concise discussion of this issue. Kurpaska (2019) offers a broader overview of how linguists classify varieties of Chinese as dialects or languages. 4 heights are what linguists call “tonal onset” and “tonal target” respectively (S. Matthews and Yip 2011, 475). For example, tone 1 (T1, the high level tone) can be represented by [55], with both tonal onset and tonal target being the highest pitch height [5]. However, linguists do not always agree on which numbers to use for some tones in Cantonese. Discrepancies between some of the numbering systems are shown in Table 1. Table 1. Different numbering systems for the six Cantonese tones Tone T1 T2 T3 T4 T5 T6 Chao (1947) [55] [35] [33] [21] [23] [22] Hashimoto (1972) [55] [35] [44] [21]/[22] [24] [33] Vance (1976) [55] [35] [33] [11] [13] [22] Bauer and Benedict (1997) [55]/[52] [25] [33] [21] [23] [22] S. Matthews and Yip (2011) [55] [25] [33] [21]/[11] [23] [22] Cheung (2016) [55]/[53] [35] [33] [31]/[11] [13] [22] Note that the numbers presented in Table 1 are theoretical abstractions, and empirical evidence does not always align tidily with these labels. By collecting acoustical data of Cantonese speech, different scholars have reported slightly different F0 profiles of the Cantonese tones. For example, by observing data reported in Lee et al. (2002), Khouw and Ciocca (2007), P. Wong and Chan (2018), and Choi (2020), one can infer that fitting tonal onsets and tonal targets into five distinct pitch levels requires a simplistic interpretation of the phonological data, since F0 in actual speech production does not adhere to a clear-cut and evenly spaced out five-pitch scale. Therefore, discrepancies between numberings are results of subjective interpretations of acoustical data, rather than evidence for significantly distinctive F0 profiles of each tone. In this thesis, I will follow the numbering system adopted in S. Matthews and Yip (2011) (shaded in blue in Table 1), since it is widely adopted in recent research, such as Choi (2020), Schellenberg and Gick (2020), and Li (2021). In this system, T4 takes two forms: a 5 level version [11] and a falling version [21]. As Flynn (2001, 12) suggested, this difference reflects inter- or intrapersonal variation and is not phonemically distinctive. More importantly, although T4 might show a falling contour in ordinary speech, it is mostly level in the context of singing (Cheung 2016, 379). Therefore, in this study I will consider T4 to be a level tone [11]. Despite variations in numbering systems and phonological data, scholars do agree on some important generalizations, as Table 1 also demonstrates: First, there are two distinct pitch contours for Cantonese tones. T2 [25] and T5 [23] are characterized by an upward contour, whereas T1 [55], T3 [33], T4 [11], and T6 [22] are level.4 Second, pairs of level and contour tones consistently have the same tonal target. For example, level T1 [55] and rising T2 [25] start on different pitch heights, but they both end on [5]. In other words, there are only four possible tonal targets for the six tones: [1], [2], [3], [5]. For tone identification in Cantonese, tonal targets are more important cues than tonal onsets (Flynn 2001, 14; P. Wong and Chan 2018, 776). Therefore, according to these four tonal targets, one can classify Cantonese tones into four registers: high for [5], mid for [3], low for [2], and extra-low for [1].5 This four-register classification reflects current understanding of Cantonese phonology and offers a coherent and well-formed system for phonological study (Cheung 2016). Recent studies in tone-melody correspondence in Cantonese have also adopted this four-register classification of tones (Ho 2010; Lo 2013; Ladd, forthcoming). This classification of tone registers will be used throughout this thesis. 4 The falling variants of T1 ([53] and [52]) reflect an old-fashioned and Guangzhou-specific pronunciation that has fallen out of use (M. K. M. Chan 1987a, 27; Bauer and Benedict 1997, 117; Gu, Hirose, and Fujisaki 2007, 33). Therefore, they are obsolete and only useful for describing the more conservative variants of Guangzhou Cantonese (Cheung 2016, 377). In addition, these four level tones (T1, T3, T4, and T6) may show a slightly falling contour due to speech declination on the syllable level, meaning that even though conceptually the tone has a level contour and is heard as such, its F0 contour could have an automatic downward trend due to physiological factors during speech production (L. Zhang 2012, 181–3). 5 Note that some earlier scholars used the archaic phonological concept of yin/yang (陰/陽) to categorize Cantonese tones (e.g., Chao [1947] and Yung [1983]). In this system, yin tones are translated into “upper,” and “yang” tones “lower.” This upper/lower classification does not correlate with pitch register consistently, so in this study I will avoid this system of categorizing Cantonese tones and will use tonal targets as the standard for pitch registers. 6 Table 2 below summarizes the above generalizations about contours and tonal targets of Cantonese tones, despite numbering discrepancies shown in Table 1. When one judges whether a song melody matches linguistic tones in its lyrics, the four distinct registers of tonal targets would play a significant role. Table 2. Generalization about contour and tonal target of the six Cantonese tones Tone T1 [55] T2 [25] T3 [33] T4 [11] T5 [23] T6 [22] Contour Level Rising Level Level Rising Level Tonal target [5] [5] [3] [1] [3] [2] Register High High Mid Extra low Mid Low While all six tones (i.e., T1–T6) are recognized as distinct in Cantonese, there are three “entering tones” which not all linguists identify as separate tones (S. Matthews and Yip 2011, 29).6 In the nine-tone system which is falling out of use, these entering tones are numbered as T7, T8, and T9. These entering tones are characterized by unreleased plosive consonants (-p, -t, -k) at the coda of a syllable. As a result, sounds of these tones end abruptly and have shorter durations, and there is no need to describe both the tonal onset and the tonal target (P. Wong and Chan 2018, 765). Therefore, Chao (1947) notated T7, T8, and T9 as [5], [3], and [2] respectively, using only one number—instead of two—to represent each tone. In other words, they are pitch-wise identical to T1, T3, and T6 respectively. Despite pitch identity with T1, T3, and T6, these checked tones are retained in the Cantonese tone inventory as remnants of Middle Chinese phonology, which classifies tones based not only on pitch, but also on consonant qualities of syllables (e.g., whether the consonant at the onset of the syllable is voiced or unvoiced) (Cheung 2016). Middle Chinese has four tones: ping (平), shang (上), qu (去), and ru (入); and ru—literally translated as “entering”—is what we now describe as entering tones. Due to the changing understanding of Cantonese phonology, many linguists have proposed to assimilate entering tones into their non-entering counterparts (e.g., Zee [1999], S. Matthews and Yip [2011], and Cheung [2016]). 6 The entering tone may also be called the “stopped” (P. Wong and Chan 2018) or “checked”(Alderete, Chan, and Tanaka 2022) tone. 7 Therefore, in this thesis I will take the six-tone system as the standard for Cantonese phonology and romanization. However, some scholars have discussed how words with an entering tone are set differently (in terms of rhythm and meaning, but not pitch) in Cantopop and Cantonese opera (e.g., Yung [1983] , M. K. M. Chan and Chey [2013], and C. W. Wong [2020]). Consequently, when encoding phonetic information of songs in the corpus, I will still mark words with entering tones as T7–9, so that claims regarding text-setting for entering tones can be examined with my corpus data in the future. When I extract data from my corpus, I convert these entering tones back into their non-entering counterparts (i.e., T7 à T1, T8 à T3, and T9 à T6), so that my analysis can focus on the role of pitch in tone-melody correspondence. 2.2. The idea of tone-melody correspondence Linguistic tone is an essential phonetic component in tone languages, in a sense that changing the tone of a word has the potential to change the word’s meaning (Schellenberg 2012, 268). When spoken in the wrong tone, words in a tone language can become unintelligible or misunderstood. In an anecdote brought up in Deutsch (2019, 182), the Mandarin sentence “I want to ask you (我想問你 wo3 xiang3 wen4 ni3)” could be embarrassingly heard as “I want to kiss you (我想吻你 wo3 xiang3 wen3 ni3)” when the verb “ask” is said in the wrong tone. (The same misunderstanding between these two sentences could arise in Cantonese as well.) In the context of singing, since words are sung on a melody with specified pitches, the lyrics could become unintelligible, misunderstood, or ambiguous in meaning if the melody conflicts with the tones. In other words, linguistic tones and the song melody should ideally correlate with each other to some extent. This correlation is commonly known as “tone-melody correspondence” (Kirby and Ladd 2016; Li 2021; X. Zhang and Cross 2021). Some scholars have used slightly different terms, such as “tone-melody matching” (Ladd and Kirby 2020), “tone-tune interface” (Wee 2019), or “tone-tune association” (McPherson and Ryan 2018), but the idea is essentially the same. 8 In order to ensure intelligibility of lyrics, there is a “text-setting constraint” in songs written in a tone language (Ladd and Kirby 2020), meaning that linguistic tones and the song melody should somewhat correspond. That is, “tone-melody correspondence” is not only a desirable aesthetic goal, but also a linguistically driven “constraint” in the song writing process. When scholars try to determine whether linguistic tones and the music match in a song setting, they compare two elements in the song: “speech melody” and “song melody” (Schellenberg 2012). Speech melody refers to pitch variations resulting from the succession of linguistic tones of the syllables. For example, Figure 1 shows the speech melody of the first line from “活着 (wut6 zoek6) Viva,”7 a Cantopop song included in my corpus. The blue lines indicate the succession of pitch heights of the tones across the six syllables of the line (when spoken). Note that all Chinese (including Cantonese) characters are monosyllabic—that is, “one character represents one phonetic syllable” (Yin 2016, 56).8 Song melody, on the other hand, consists of the somewhat definite pitches from the music to be sung, as would be notated on a score with staff notation. Figure 2 shows the transcription of the song melody from the same line as Figure 1. Note that, in this line, the speech melody and the song melody show the same contour. Figure 1. Speech melody of the first line from “活着(wut6 zoek6) Viva” 7 Numbers following Cantonese romanizations are tone numbers (i.e., T1–6). Romanization and tone category of syllables will be in parentheses. On the other hand, pitch heights in terms of Chao numbers [1] through [5] will be presented in square brackets. 8 That all Chinese characters are monosyllabic does not mean all Chinese words are monosyllabic. See Ceccagno (2016) for a description of the development of disyllabic and polysyllabic words in Chinese. 9 Figure 2. Transcription of the first line from “活着(wut6 zoek6) Viva” As words and notes are sung in a song, each sung note of the speech melody and the song melody can each proceed in three directions: up, down, or level (i.e., staying on the same pitch). When these directional movements are observed across syllables in both melodies, one can describe the resulting motion as “similar”, “contrary”, and “oblique”, adapting terminologies from counterpoint theory (Ladd and Kirby 2020, 678). When the two melodies move in the same direction, they are in similar motion.9 When they move in different directions, they are in contrary motion. Oblique motion describes the case where one of the melodies stays level while the other moves either up or down; it can be further divided into types I and II, depending on whether it is the speech melody (Oblique I) or the song melody (Oblique II) that moves (Ladd and Kirby 2020, 678). Table 3 summarizes these contrapuntal relationships between speech melody and song melody, adapted from the format presented in Ladd and Kirby (2020). Using the concepts of speech and song melodies and the three types of contrapuntal motion between the melodies, researchers approach the issue of tone-melody correspondence in tone languages by observing “sequential pairs of musical notes and the accompanying syllables,” also known as “bigrams” (Ladd, forthcoming). For example, Table 4 juxtaposes the speech and song melodies from Figures 1 and 2 and shows the five resulting bigrams (labelled A–E) within the line and their respective contrapuntal motions. Bigrams serve as data points in studies of tone-melody correspondence in tone languages. By analyzing patterns in the 9 Some studies (e.g., Schellenberg [2012], McPherson and Ryan [2018], and Pooley [2020]) use “parallel” and instead of “similar” motion to describe the case where speech melody and song melody move in the same direction. However, since in counterpoint the term “parallel” has the extra connotation of an equal magnitude of change in both melodies, which is not necessarily the case, I will adopt “similar” as the better description in this study. 10 resulting data, researchers make conclusions about the degree and patterns of tone-melody correspondence in the songs being studied. Table 3. Summary of contrapuntal relationship between speech and song melodies Table 4. Bigrams in the first line from “活着 (wut6 zoek6) Viva” While observations vary across languages and genres, the text-setting constraint is manifested through a hierarchy of preferences. First and foremost, the most basic form of the text-setting constraint comprises “the avoidance of contrary motion” between the speech melody and the song melody (Ladd and Kirby 2020, 679). This aspect of the text-setting constraint has been explored extensively in previous research. By comparing the proportion of contrary motion and the other types of motion, researchers can describe how strong the text-setting constraint is in a particular language. Researchers have found evidence of this constraint 11 in many tone languages, such as Chaozhou (X. Zhang and Cross 2021), Kammu (Karlsson 2018), Thai (Ketkaew and Pittayaporn 2014), Tlahuapa Tù'un Sàví (Sleeper and Basurto 2022), Tommo So (McPherson and Ryan 2018), Vietnamese (Kirby and Ladd 2016), and Zulu (Pooley 2020). Nonetheless, the strength of this constraint varies greatly across languages and genres: linguistic tones and musical pitches correspond more closely in some languages (e.g., Cantonese and Zulu) than others (e.g., Kalam Kohistani and Shona) (Schellenberg 2012; McPherson and Ryan 2018). However, the avoidance of contrary motion is only the basic form of the text-setting constraint; in some languages there is a stronger constraint of preferring similar motion (Ladd and Kirby 2020, 679). This leaves oblique motion with an in-between status: it is more acceptable than contrary motion, but less preferable as similar motion. Oblique settings are weakly avoided in the case for some languages (McPherson and Ryan 2018), but not universally (Kirby, forthcoming). In sum, the text-setting constraint for tone languages consists of a hierarchy with three levels, listed below from the most basic constraint to the strictest: (1) the strong avoidance of contrary motion, (2) the weak avoidance of oblique motion, and (3) the preference for similar motion. Notably, although linguistic tones may influence the direction of song melodies, in some musical traditions “they do not ultimately determine melodic contour” (Agawu 2016, 126). Contours of song melodies are nevertheless still influenced by extralinguistic considerations, such as the conventional musical syntax and expressive demands for the song. In the next section, I will lay out details about methodologies employed in studies of Cantonese songs and observations specific to the language. 12 2.3. Tone-melody correspondence in Cantonese—A historical and methodological overview In 1983, Bell Yung published the first major study concerning tone-melody correspondence in Cantonese music in the journal Ethnomusicology, some fifty years after the earliest scholarly attempt to theorize the relationship between linguistic tones and song melody (Herzog 1934). In his inquiry (1983), Yung studied melodic patterns in one of the standard “aria types” (梆黃) in Cantonese Opera. In this aria type called “chat-ji-ching” (七字清), vocal lines adhere to a melodic formula according to which many musical elements are invariant; therefore, by comparing nine different realizations of the same melodic formula, Yung was able to conclude that “the specific pitches and the melodic contour of the aria type are to a great extent determined by the linguistic tones of the text” (1983, 39). Soon after Yung’s pioneering research which examines Cantonese opera, his analytical approach was adopted for studying Cantopop melodies. Marjorie K. M. Chan (1987a; 1987b) compared verses of six Cantopop songs that were released between 1984 and 1986 and examined how different texts were written for the same melody at different iterations of the verses. Subsequently, more scholars have tried to reconsider the relationship between tone and melody in Cantopop by analyzing passages from newly chosen sets of songs. Table 5 below lists studies based on analysis of Cantopop examples and the number of examples examined. Following M. K. M. Chan (1987a; 1987b) and P. C. M. Wong and Diehl (2002) which have examined small samples of songs, more recent studies have attempted to examine the issue of tone-melody correspondence more comprehensively, but methodological problems persist. Methodological shortcomings of these studies will be elaborated in Chapter 3. Among these analysis-based studies, only P. C. M. Wong and Diehl (2002), Lo (2013), and Kirby (forthcoming) have adopted a quantitative approach, producing statistics based on counts of all bigrams in their samples. Other researchers used their samples in an ad hoc manner, highlighting selected passages only to support specific arguments. 13 Table 5. Analysis-based studies and number of Cantopop examples examined Study Examples examined Number of bigrams Chan (1987a; 1987b) Verses from 6 songs / P. C. M. Wong and Diehl (2002) 4 songs 281 Ho (2010) Selected passages from 50 songs / Chow (2012) Selected passages from 33 songs / Lo (2013) 11 songs 2,665 Li (2021) 2 songs / Kirby (forthcoming) 8 songs (plus Mandarin renditions of the songs) 1,720 In addition to published studies based on close analysis of specific Cantopop examples, some other scholars approached the issue of tone-melody correspondence in Cantonese by conducting experiments with Cantonese speakers. Researchers have wanted to verify analytical findings by designing experiments which require Cantonese speakers to say, sing, or listen to certain strings of Cantonese speech or melodies. P. C. M. Wong and Diehl (2002) were the first to use such experiments, followed by scholars such as Ho (2010), Yiu (2013), Schellenberg and Gick (2020), and K. Y. Chan (forthcoming). Apart from the abovementioned scholarly publications, Chi Wah Wong’s (2020) monograph offers an alternative perspective about the topic of tone-melody correspondence in Cantonese. Wong is a lyric critic focusing on Cantopop and a pedagogue on lyric writing for the genre. Based on his practical experience (rather than systematic study of musical examples or empirical evidence), he deduced a set of rules for lyricists so that linguistic tone and song melody are “coordinated” (協音) (C. W. Wong 2020, 22). Therefore, he approaches the topic not really as a scholar, but more as a practitioner, and the resultant theory is more prescriptive rather than descriptive. Nonetheless, despite the diverging motivations and methodologies, some of Wong’s rules do resemble findings reported by scholars through analyses and experiments. For example, Wong’s idea of the “most natural combinations” (最自然結合) of speech and song melodies reflects the preference for similar motion (2020, 27–28), whereas his 14 “principle of same direction” (同向原理) describes the viability of oblique motion in Cantopop text-setting (2020, 129–42). These principles of Wong’s are consistent with the description of the text-setting constraint as discussed above. While the above paragraphs offer a historical and methodological overview of research on tone-melody correspondence in Cantonese, findings from previous studies will be reported and examined in greater detail in the following chapters, as I focus on specific research questions, which are outlined in Chapter 3. 15 3. Methodology 3.1. Research objectives and questions As mentioned in Section 2.3, in previous studies on tone-melody correspondence in Cantonese, the size of song samples is often small (see Table 5) and few researchers have attempted to analyze the examples quantitatively and systematically. Ho (2010) and Chow (2012) tried to include a larger number of musical examples from more Cantopop songs, but they only used selected passages from each song in their analyses. The criteria for selecting the passages and the songs are not clearly identified. Consequently, the findings in the studies did not stem from a rigorous methodology. The researchers might have handpicked songs or passages that demonstrate specific musical or linguistic properties, making it unclear whether these observations are representative of Cantopop text-setting in general. To date, Lo’s (2013) investigation is probably the quantitative study that has sampled the greatest number of complete Cantopop songs, examining all bigrams from the 11 songs he picked. However, the representativeness of his song sample is not sufficiently justified. He selected songs written by eight different lyricists,10 attempting to minimizing the impact of “individuality in usage or realization of words” (p. 19). Nonetheless, he did not explain how the songs were chosen from the lyricists’ oeuvres or how the eight lyricists were selected, so certain avoidable biases might still exist in his selection, such as his preferences for certain singers and lyricists. Similarly, Kirby admitted that the eight-song corpus used for his study was chosen “opportunistically” without considering the representativeness of the songs in relation to the genre (forthcoming). In short, since the data in published studies are collected from small samples whose representativeness remained inconsistent or ill-defined, one cannot inductively infer that conclusions from previous research are also applicable to a larger corpus of Cantopop. 10 The eight lyricists are Lin Xi, Wyman Wong, Dash Tam, Sandy Chang, Abrahim Chan, Riley Lam, Adrian Chow, and John Laudon. 16 To tackle the problem of small sample size and unrepresentative sampling, I propose to study tone-melody correspondence in Cantopop with a rigorously designed corpus study. With the aid of computing technology, I will be able to extract data from a much larger sample of songs. In addition, although the method of corpus research does not guarantee the absence of bias and errors (Marsden 2022), any source of potential sampling bias in this study is open to scrutiny. Hence, I explicitly outline the criteria for selecting the songs (see Section 3.2). In sum, by constructing and examining the first large and representative corpus of Cantopop, I identify and thus address the methodological problems related to size and bias found in earlier studies. The total number of bigrams from the 105 songs in my Cantopop corpus amount to 31,482. Thus, my study offers a more-than-tenfold increase in sample size relative to the previous quantitative studies in the topic of tone-melody correspondence in Cantopop (cf. Table 5). As my sample is selected based on the more carefully defined selection criteria, my corpus will provide substantial evidence that support, challenge, and complement earlier claims about the topic, and make original claims and questions that have not been made. To this end, this thesis will examine the two following issues about tone-melody correspondence in Cantopop. In Chapter 4, I investigate how contour tones are set in Cantopop. I critically examine the widespread assumption that contour tones and their level tone counterparts are treated as equivalent—this assumption is sometimes known as the “endpoint principle.” Supported by data extracted from my corpus, I supplement the endpoint principle by pointing out how contour tones may be set more flexibly than their level tone counterpart. In Chapter 5, I revisit questions related to oblique motion in Cantopop text-setting. I examine the role of oblique I motion in relation to the text-setting constraint and consider the role of pitch register in the directionality of oblique II motion. In Ladd’s words (forthcoming), these two issues have remained “poorly understood” (p. 1) in the study of tone-melody correspondence across tone languages. By offering newly available evidence from my original corpus, this study will enhance the understanding of contour tones and oblique motion in tone-melody correspondence in Cantopop. 17 3.2. Construction of corpus Corpus studies of music can improve the reliability and validity of the research outcome, but the selection of the corpus contents must be carefully carried out in order to avoid bias and incorrect results (Marsden 2022). Since the current study requires the construction of a new corpus of Cantopop, I must clearly outline the rationale behind my selection. Following the recommendations by London (2013) and Marsden (2022), I construct the Cantopop corpus with reference to multiple sources of information, instead of drawing the list of songs from a single source. London (2013) described a statistically refined and genre- and composer-conscious methodology for constructing a corpus of classical music. He referred to multiple sources such as music history textbooks, concert programs, and lists of audio recordings on sale, so that the resulting corpus would represent the diverse range of contexts in which classical music is heard. On the other hand, some corpus studies in popular music have been relatively less rigorous in terms of the use of sources. For example, de Clercq and Temperley (2011) and Temperley and de Clercq (2013) compiled their 100- and 200-song rock corpora from one single source—the list of “Greatest Songs” from the Rolling Stone magazine. Callahan’s (2013) study on phrase types is based on 207 songs by five “representative composers” from the Great American Songbook, though without elaborating on how the composers or songs were selected. Summach’s (2011) larger sample of 700 songs is based on Billboard Annual Top 20s from 1955 to 1989. Similarly, White, Pater, and Breen’s (2022) corpora of postmillennial songs consists of 25 top-ranked songs from the Billboard Top 100s across five years. In short, popular music corpora are often compiled from one single source and take the representativeness of the sources for granted, as the representativeness of these charts is already widely recognized and does not need critical scrutiny. However, this assumption is not immediately applicable to the study of Cantopop. The approach of relying on media sources and critics’ reviews is convenient, but not foolproof. Sometimes these song charts could be prejudiced by personal preferences of editors 18 and disc jockeys who produced the charts, and may not represent a majority opinion as to whether a song is sufficiently popular within the market segment (de Clercq and Temperley 2011, 51). These assumptions and conditions that lead to the issue of “representativeness” must be identified when I compile a rigorous Cantopop corpus for this study, especially when none at scale has been constructed yet. Although Cantopop is a global genre—in terms of the use of the Cantonese language in various diaspora communities worldwide and not by a particular geographical location—Hong Kong has been a focal point where it originated and maintained cultural dominance (Chu 2017; A. Fung and Chik 2020).11 Radio and TV outlets in the city have been important media for the dissemination of Cantopop since the 1960s, the dawn of the genre (Chu 2017). As listed in Table 6, three radio stations and one TV channel (the only fully functioning free TV channel during the period 1978–2016) have held annual song awards ceremonies since the 1970s. Table 6. The four major media outlets and their song awards (Chu 2017) Media Outlet Annual Awards Ceremony (Launch Year12) Commercial Radio Channel 2 商業電台第二台 (CR2) Ultimate Song Chart Awards Presentation (1988) 叱咤樂壇流行榜頒獎典禮 Radio Television Hong Kong 香港電台 (RTHK) Top 10 Gold Songs Awards (1978) 十大中文金曲 Metro Radio 新城知訊台 (Metro) Hit Awards (1994) 新城勁爆頒獎禮 Television Broadcasts 無綫電視 (TVB) Jade Solid Gold Best Ten Music Awards Presentation 勁歌金曲頒獎典禮 (1983) Criteria for giving out awards include combinations of airplay frequency, fans’ votes, and some adjudication preferences internal to each institution that administers each chart (Chu 2017, 102; Chung 2001). Nonetheless, these pieces of information and statistics concerning 11 In places where a sizeable Cantonese-speaking population is present, there are Cantopop charts that keep track of the local popularity of Cantopop. For example, the Vancouver-based Fairchild Radio hosts the weekly Canadian Chinese Pop Music Chart, which consists mostly of Cantopop. The comparison of these charts targeting Cantonese-speaking diaspora would be relevant and valuable for global Cantonese study. Nonetheless, these comparisons are out of the scope of this thesis. 12 The award presentations typically take place after the turn of the year: for example, the first RTHK Top 10 Gold Songs Awards ceremony took place on February 20, 1979 for songs released in 1978. 19 internal operations, as well as other external factors such as advertising revenues and recommendations by record companies, are rarely made clear to the general public. To construct a rigorous corpus and to understand the meanings of “representativeness” in Cantopop study, I gathered a preliminary set of songs (hereafter “Preliminary Set”) which comprises all awarded songs in the four awards ceremonies for the years 2000–2020. Various types of awards are presented at each awards ceremony, and the Preliminary Set only includes songs awarded in the “annual top songs” category. The starting year of 2000 is chosen arbitrarily and may be moved forward in upcoming attempts to study Cantopop from an earlier date. The exclusion of songs after 2020 is prompted by changes in the mass media industry in Hong Kong. In 2021, notably, ViuTV (a TV channel established in 2016) started its own song awards, whereas RTHK and TVB decided to merge their respective awards ceremonies. Impact of these developments on the assessment of popularity and representation has yet to be determined. To prevent these factors from jeopardizing the consistency of my data set, this study will adopt the year 2020 as a cutoff. There are 728 distinct songs in the Preliminary Set.13 While the number of awards given out by each channel each year ranges from 10 to 22, the size of the Preliminary Set (N = 1,116) is smaller than the gross total of awards given out during the period, due to overlap between songs awarded at the four channels. That is, for example, songs receiving an award at CR2 may also be awarded at RTHK, Metro, or TVB, or any combination of the remaining three. Figure 3 visualizes the distribution of awarded songs in the Preliminary Set among the four channels. Percentages indicate the respective proportions in the Preliminary Set. 481 songs are singletons, receiving awards only at one channel. The remaining songs have received awards at two or more channels, with 38 being awarded at all four. Table 7 demonstrates the breakdown of the Preliminary Set by year and number of awards each song receives. 13 The complete song list is available on this project’s GitHub repository: https://github.com/jasonleeubc/Cantopop-corpus 20 Figure 3. Distribution of awarded songs among the four channels in the Preliminary Set14 The corpus for this study is constructed by selecting five songs per year from the Preliminary Set, producing a 105-song corpus (5 × 21). Since this study aims to study the general phenomenon—but not the within-corpus trend—of tone-melody correspondence, the relatively small number of songs chosen from each year is adequate for this study at this stage. This small sample size selected per year also makes this study feasible while enabling a method to be reproducible and expandable for a later phase of research. Regarding the overall sample size, each song would already contain hundreds of bigrams (i.e., data points to be analyzed in this thesis). Hence, as it is the number of bigrams that each song comprises—and not the number of songs per se—that constitute datapoints for this study, this 105-song corpus would yield a sufficiently large sample for statistical analysis. 14 Created with the online tool “Venny 2.1” (https://bioinfogp.cnb.csic.es/tools/venny/) 21 Table 7. Breakdown of the Preliminary Set by year and number of awards each song receives Number of songs receiving n awards Total of awarded songs Year n = 4 3 2 1 2000 3 4 5 18 30 2001 4 6 2 12 24 2002 3 6 2 18 29 2003 3 3 8 14 28 2004 3 3 8 14 28 2005 5 1 4 20 30 2006 3 5 4 18 30 2007 4 3 5 15 27 2008 2 1 8 25 36 2009 1 6 6 18 31 2010 0 2 10 27 39 2011 0 5 9 21 35 2012 1 0 10 28 39 2013 1 4 10 26 41 2014 2 4 5 33 44 2015 1 1 12 32 46 2016 1 3 7 25 36 2017 0 3 9 25 37 2018 0 2 9 30 41 2019 0 1 5 35 41 2020 1 2 6 27 36 Total 38 65 144 481 728 The selection process aims to ensure wide representativeness of the corpus by choosing songs with the greatest and most widespread popularity, with the number of awards received by each song taken as publicly available evidence for popularity. The procedures for selecting the songs are as follows: 1. For each year, songs that are awarded at all four channels (i.e., from the “n = 4” column in Table 7) are included in the corpus. The maximum number of four-award songs in any year in the time range is five, so all 38 four-award songs in the Preliminary Set are included in the corpus (see below for exceptions). 22 2. For years with fewer than 5 four-award songs (i.e., all except 2005), three-award songs are selected to make up for the shortfall. If the total number of three-award songs exceeds the remaining quota for the year (e.g., for the year 2000, 2 three-award songs are to be selected from a subtotal of 4), the requisite quantity of three-award songs is fulfilled by using a randomizer to make the selection at random. 3. After steps 1 and 2, if there are still fewer than five songs selected for a particular year (e.g., 2010 and 2012),15 two-award songs are chosen randomly to complete the five-song set for the year. Apart from the above procedures that select the most widely recognized songs, there are factors that would warrant a song’s exclusion from the corpus. The first category of songs to be excluded is duets or songs sung by groups. When two or more singers have prominent lines of their own—whether the resulting texture is homophonic, heterophonic, or polyphonically—the interaction between speech melody and song melody is more complex.16 Such instances should be reserved for a follow-up study. Therefore, duets and group songs are excluded from this study, unless both singers sing entirely in unison (or octaves) or their lines do not overlap at all. (For example, in the corpus, the songs “天梯 (tin1 tai1)” and “逾越生死 (jyu4 jyut6 sang1 sei2)” sung the boy band C Allstar belong to this case and are included in the corpus; the singers always sing in unison throughout the songs.) Rap songs constitute the second category to be excluded. Although pitch does play a salient role in rap music, pitch content in rap cannot be practically transcribed in Western staff 15 From Table 7, one can notice that the number of four- and three-award songs dropped drastically after 2009, and the count of singleton one-award songs has been high. This is likely due to a commercial dispute between record labels and media outlets, which resulted in the TVB awards boycotting some record labels. This controversy has led to more fragmented and polarized preferences across different awards. See Chu (2017, 181–83) for a description of the controversy and K. Chan, Ng, and Sea (2022, 77–87) for a discussion on the declining representativeness of the TVB awards. 16 Tsui (2018, 35–44) offers a discussion on the interaction between vocal lines in Cantopop duets. Such interaction can also be seen in Cantonese choral music, where only the overall intelligibility of the superimposed vocal parts—but not individual lines—matters (K. Y. Chan, forthcoming). See K. Y. Chan (forthcoming) for more examples of this interaction in Cantonese choral music. 23 notation (Ohriner 2019; Komaniecki 2020). Since the transcription of this corpus relies on staff notation (see Section 3.4), rap-based songs are excluded from the current study, whereas future studies that do not rely on staff notation should certainly look into the genre of Cantonese rap. Last and obviously, songs not sung primarily in Cantonese cannot be included. Mandarin songs are present in the Preliminary Set, albeit as a minority. (Out of the 728 songs in the Preliminary Set, 17 are sung in Mandarin.) However, this does not mean to exclude Cantonese-based songs that feature occasional code-switching (mostly between Cantonese and English), which is an important feature of Cantopop since its genesis (B. H.-S. Chan 2009; Chik 2010; Ng 2021). Songs with code-switching can be included in the corpus and transcribed fully, although passages not in Cantonese will be omitted from my computation and analysis. The above selection procedure and exclusion criteria have yielded a corpus of 105 songs, which is listed in Appendix A. Melodic, textual, and phonetic information from these songs is transcribed and stored also in this project’s GitHub repository.17 Before proceeding to outline the principles of data transcription, I shall discuss some notable issues of representation and diversity in the corpus. 3.3. Issues of representation in the corpus Figure 4 shows that the two most represented lyricists—Lin Xi (林夕) and Wyman Wong (黃偉文)18—have 34 and 28 works included in the corpus respectively, accounting for more than half of the 105 songs. This finding reflects the reality of the Cantopop industry, where these two lyricists have dominated the field of lyrics-writing of post-1997 Cantopop for more than a decade (Chu and Leung 2015, 15).19 17 See footnote 13 (p. 17) for the hyperlink to the GitHub repository. 18 English translation of Cantonese names follow Chu’s protocol (2017, x), adopting the first name–last name format in colloquial Cantonese romanization, unless other commonly known names exist. One exception is the name of the lyricist Lin Xi (林夕), which is based on the name’s Mandarin romanization and uses a last name–first name format. 19 With a considerable size these two lyricists’ oeuvre, it is worthwhile for a future study to investigate if they have different approaches to setting lyrics in Cantopop. 24 Figure 4. Distribution of lyricists in the corpus As shown in the Figure 5, the two most represented singers in the corpus are Joey Yung (容祖兒) and Eason Chan (陳奕迅), each with 11 and 10 songs respectively. They together account for one fifth of the corpus’ song count. This observation is again indicative of the Cantopop industry during the two decades in question. Joey Yung and Eason Chan were arguably the “last megastars” of Cantopop amid the gradual shrinkage of the Cantopop market in the new millennium, even though their popularity did start to wane gradually after the early 2010s (Chu 2017, 158–62). These distributions of lyricists and singers in the corpus depict an accurate picture of the Cantopop industry during the decades covered by this study. Figure 5. Distribution of singers in the corpus 34(32.38%)28(26.67%)9(8.57%)5(4.76%)4(3.81%)25(23.81%)Lin XiWyman WongRiley LamAbrahim ChanSandy CheungOthers11(10.48%)10(9.52%)6(5.71%)6(5.71%)6(5.71%)6(5.71%)60(57.14%)Chart TitleJoey YungEason ChanAlfred HuiHacken LeeLeo KuMiriam YeungOthers 25 3.4. Data transcription and related issues In the previous sections, I have outlined the selection criteria for the Cantopop corpus and examined whether the selected songs constitute a representative picture of the genre during the period 2000–2020. Having established the representativeness of the corpus, in this section I discuss how the corpus data is transcribed and interpreted to allow further analysis. In this study, tone and musical data in the corpus are analyzed with Humdrum Toolkit, an open-source software created by David Huron in the 1980s.20 To prepare the songs for analysis, I have transcribed textual and melodic information of the songs with Verovio Humdrum Viewer (VHV), an online music editor developed by Craig Sapp in 2017.21 The VHV interface allows one to input musical data in Humdrum format and instantly renders the music graphically in Western staff notation. Figure 6. First 22 lines of Humdrum representation of “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102) 20 An online manual of Humdrum Toolkit can be found on https://www.humdrum.org/. See also Wild (1996), Huron (2002), and Cook (2004) for a description of Humdrum’s functionality. 21 VHV is accessible at https://verovio.humdrum.org/. Its documentation is available at https://doc.verovio.humdrum.org/. 26 Figure 6 gives an example of a Humdrum representation of a song. The first eight lines contains reference records, listing song title, an assigned song ID (consisting of the character “C” + last two digits of the release year + an arbitrary ordinal number of the song within the year), release year, and names of singer, composer, lyricist, arranger, and producer (in this order). As line 9 in Figure 6 indicates, data of each song are stored in three vertical “spines” in **kern, **text, and **IPA representations. They represent melodic, textual, and phonetic information respectively. Only information relating to the vocal melody is transcribed—that is, instrumental parts are excluded. Therefore, transcription of each song begins with the singer’s entry and ends with the last line of vocal melody. Phonetic information of the song is recorded in Jyutping, the Cantonese romanization scheme standardized by the Linguistic Society of Hong Kong and last updated in 2022. Although Jyutping adopts the more common six-tone system for classifying Cantonese tones, entering tones in this corpus are still notated distinctively as tones 7–9 (see Section 2.1 for the rationale behind this editorial decision). Lines 10–14 of the **kern spine contain information regarding clef, key signature, key, meter, and tempo respectively. Even though only melodic, textual, and phonetic information of the songs are transcribed in the corpus, some aspects of transcription are less straightforward than expected and require closer scrutiny. In the following paragraphs, I will examine three of such issues—relating to tonality, phrasing, and melismatic text-setting. For these issues, there is no one-size-fits-all or cut-and-dry solution, and an ad hoc editorial decision is required. As Doll elegantly put it, in the study of popular music, “transcription is a part of—not prior to—analysis” (2018, 5). Decisions regarding these problems are provisional and currently tailored to suit research questions of this study. For future research using this corpus to examine other aspects of Cantopop, one must note these caveats, and some modification of the transcribed data is likely necessary. These issues are discussed as follows: 27 Issue 1: Tonality Key identification of each song is a relevant issue for this corpus because some scholars have examined the role of scale degrees in tone-melody correspondence in Cantopop (Ho 2010; K. Y. Chan, forthcoming). Although the elements of key and scale degrees are not included in this study, for further studies that wish to use this corpus to study this issue, it will be important to understand how tonality is currently identified for each song. Chord progressions in popular music commonly lead to ambiguity when it comes to key identification (e.g., see Biamonte [2010]; Doll [2017, 215–61]; Richards [2017]; Spicer [2017]). As a result, determining tonality in popular music can be tricky, particularly when the song features a “double-tonic complex” formed by the coexistence of relative major and minor keys (Nobile 2020). More recently, Nobile (2020, 222–23) has described the problem not as one of tonal ambiguity, but of indeterminacy: the relative keys are not mutually exclusive, but rather intertwined and blended together. In light of this problem, de Clercq (2021b) offered the “six-based” approach as the solution for analyzing songs that involve such indeterminacy between relative keys. With the six-based approach, analysts take the minor tonic as scale degree 6!, whereas in the “one-based” approach—generally used in analyzing classical music—the minor tonic is taken as scale degree 1!. In corpus studies of popular music, the six-based approach may offer a better picture of harmony in popular music, since the six-based approach can better accommodate the intertwining of relative keys than the one-based approach, which most popular musicians do not recognize in the first place, as de Clercq (2021a) pointed out. While de Clercq’s observation may be limited to musicians writing Anglo-American popular music, the same is also true for Cantopop songwriting, as substantiated by sketches recently published by Lin Xi the lyricist (Lin 2022). Therefore, in this study, key labels of all songs are given in the relative major. In Cantopop, the natural minor collection is the prevailing form of the minor mode used in Cantopop songs (Yang and Yu 2013, 31). In such cases, even when the minor side of the double-tonic complex is explored more extensively in a song, the pitch collection is still identical 28 to that of the relative major. Accordingly, when working out scale degree information, Humdrum Toolkit will be correctly labelling major-based passages and adopting the six-based approach for minor-based passages at the same time. This certainly does not mean to claim that all Cantopop songs are written in the major mode; this is but an editorial decision that serves to produce applicable data for this research. Issue 2: Phrasing Phrasing is another complicated aspect in popular music analysis (e.g., see Attas 2011; Moore 2012, 56–64; Robins 2017). One’s decision on phrasing always reflects some underlying research agenda: for example, while trying to demarcate phrases, an analyst might want to focus on the role of the singing voice or the instrument (Attas 2011, para. 3), the sense of tonal motion (Rothstein 1989, 5), or the notion of closure (Robins 2017). For the purpose of this study, the focus of phrasing is on the text. Since the basic form of the text-setting constraint is the avoidance of contrary motion (see Section 2.2), previous research has investigated the conditions for the occurrence of contrary motion in Cantopop. While contrary motion is found only sparingly in Cantopop, it is mostly found at “prosodic boundaries” (Ho 2010, 71). In Ho’s terms, prosodic boundary refers to the boundary between syntactic units in a sentence (2010, 58–59). Although some linguists argued that there is a subtle distinction between syntactic and prosodic units (Bennett and Elfner 2019), Ho regarded them as equivalent. Ho suggested that the directionality constraint of avoiding contrary motion is “waived” and can be violated at syntactic boundaries (2010, 57–58). Subsequently, Lo (2013) has substantiated this claim by reporting that all instances of contrary motion in his corpus are found across syntactic boundaries. Since syntactic boundaries are drawn by linguistic syntax that is hierarchical, parsing possibilities exist on multiple hierarchical level—for example, by word cluster, grammatical phrase, clause, or sentence (van Gompel and Pickering 2012), and it would be impossible to consider them all in the transcription. 29 Therefore, my approach to phrasing is to follow the lineation of the lyrics—that is, how the text is divided into smaller units. Like poetry, lyrics in popular music are often organized in lines and stanzas (BaileyShea 2021, 101), and Cantopop is no exception. However, unlike English songs and poems which use punctuation to demarcation phrase segments, those written in Chinese (including Cantonese) use within-line spaces for phrase delineation (Xu 2018). In this study, these spaces and line breaks in the lyrics will mark phrase boundaries in the transcribed lyrics.22 However, in cases where exceptionally long lines are not separated by spaces, the singer’s breaths would serve as a secondary indicator for phrase segmentation. This approach is consistent with previous analytical studies in popular music, where singers’ breath is sometimes taken as an indicator of phrase boundaries (Attas 2011, paras. 2–3). 1. 2. 3. 4. 大世界像舞台 daai6 sai3 gaai3 zoeng6 mou5 toi4 換節目所以沒往來 wun6 zit3 muk6 so2 ji5 mut6 wong5 loi4 彼此繁忙另投最愛 bei2 ci2 faan4 mong4 ling6 tau4 zeoi3 oi3 誰投錯票說你共我應該不會分開 seoi4 tau4 co3 piu3 syut3 nei5 gung6 ngo5 jing1 goi1 bat1 wui5 fan1 hoi1 Figure 7. Lyrics of the first prechorus in “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102) with Jyutping As an illustration of my principle of phrasing, Figure 7 shows lyrics of the first prechorus in “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102) and its delineation, while Figure 8 is the transcription of the passage after phrase boundaries are encoded in VHV. As shown in Figure 7, the lyrics of this passage are originally divided into four lines. But in the music, there are rests in lines 3 and 4, with an asterisk marked above them in Figure 8. Breaths 22 Spacing and line break information is taken from subtitled music videos uploaded to YouTube in the singer’s/record label’s official channels. If that information is unavailable, lyrics for the song provided by Spotify for the song serve as an alternative source. 30 are taken at these two points, so both lines 3 and 4 are broken into two phrases. Accordingly, there are six phrases in this section, as indicated by the square brackets in Figure 8. Figure 8. An excerpt of the first prechorus of “最愛演唱會 (zeoi3 oi3 jin2 coeng3 wui2)” (C0102), including phrasing and Jyutping Issue 3: Melismatic text setting As mentioned above in Section 2.3, investigations into tone-melody correspondence in Cantonese music began with Yung’s (1983) study on Cantonese opera. Major sung components in Cantonese opera include “fixed tunes” and “aria types,” many of which feature florid and lengthy melismas (Yung 1989). As the first scholar to systematically study this issue, Yung picked an aria type that is mostly syllabic, showing the rigor in his research method. As a result, there is a one-to-one mapping between linguistic tones and melodic pitches in most passages he analyzed, since each syllable is sung on only one pitch. This would make determining the melodic interval between syllables a straightforward task, which would have been made complicated if multiple pitches were set to one syllable. In his subsequent monograph (Yung 1989), he did not expand his investigation into the melismatic aria types, only noting that the issue of tone-melody correspondence would “involve different and additional factors” in melismatic passages (p. 90). 31 While Cantonese operatic music often features lengthy florid melismas, Cantopop is predominantly syllabic. Nonetheless, melismatic syllables are still present in a small but considerable quantity. In the 105 songs of my corpus, 2.80% of all syllables (1,062 out of 37,877) are set melismatically. Despite research progress in the past decades, scholars have yet to settle on how to analyze melismatic syllables regarding tone-melody correspondence in Cantopop. P. C. M. Wong and Diehl (2002) decided that, without offering any explanation or evidence, only the final pitch in two-note melismas would be considered in their analysis and the initial note should be ignored. To follow up on this matter, Ho carried out a “simple perception test” with one passage from a Cantopop song (2010, 51),23 and her results contradict what P. C. M. Wong and Diehl (2002) suggested. She concluded that it is the initial instead of the final pitch of a two-note melisma that is relevant for the perception of tone-melody correspondence. This relevant pitch within a melisma is what Ho called the “mapping locus” (2010, 50). In a more organized attempt to solve this problem of finding the mapping locus, Chow (2012) examined and compared passages from three Cantopop songs. She found that it is possible that either the initial or the final pitch of melismatic syllables could serve as the mapping locus. Although Chow managed to point out that the location of pitch is not a decisive factor, she stopped short of offering a better suggestion for locating the mapping locus within a melisma. In sum, the current status of research shows no consensus about how a mapping locus can be determined within a melismatic syllable. But obviously, there is more at play than the position of a pitch, since examples offered in previous studies show that a mapping locus can be found in different positions within a melisma. In this study, I will identify mapping loci in melismatic syllables based on melodic functionality. As Malawey (2020) noted, the function of melismas in popular music is to embellish the vocal melody. In A Generative Theory of Tonal Music (GTTM), Lerdahl and Jackendoff concisely described the perceptual hierarchy between structural and embellishing 23 Ho offered minimal details about this experiment; she did not mention the number of participants involved in the test, a statistical summary of the results, or how the musical excerpts were prepared. 32 pitches: “If a pitch is heard as ornamenting another pitch, it is felt as structurally less important than the other pitch—it is subordinate to the other pitch. In short, the pitch relations involved […] are hierarchical.” (1983, 106). Therefore, in a melisma, there are notes that fulfil an embellishing function—that is, notes that are ornamental in nature and do not belong to the music structurally—and notes that are structurally more important. By distinguishing between embellishing and structural pitches in a melisma, I will take the structurally most important pitch as the mapping locus. Of course, this assumption of equating structural importance of pitches with their perceptual significance has yet to be tested experimentally in the specific context of Cantonese tones, but the GTTM has made a strong case for the relative structural importance of pitches, which “has long been acknowledged as a psychologically important phenomenon” (Lerdahl and Jackendoff 1983, 111). I classify melismatic syllables into three categories. The first type is what I call the portamento-type melisma, borrowing the term from classical singing technique. In a portamento, the singer carries their voice from one note to the next, thus anticipating the next note while staying on the vowel of the current syllable (Potter 2006, 527). For example, in Figure 8 above, the penultimate syllable “分 (fan1)” is set over a melisma of A4–G4, with the G4 being an anticipation of the note on which the final syllable “開 (hoi1)” is sung. In such cases, because the second pitch is only an anticipation of the next syllable, the first pitch (A4 in the example in Figure 8) is structurally more important and will be taken as the mapping locus. The second type is the end-of-phrase melisma, which constitutes a virtuosic display of the singer’s “vocal motility” at the end of a phrase (Malawey 2020, 79–80). Unlike the portamento-type, these end-of-phrase melismas often involve more than two notes. The presence of these virtuosic melisma in Cantopop echoes what Yung (1983) observed in Cantonese opera, where a predominantly syllabic aria type can still have florid melismas at the end of a line. In these instances, the melisma elaborating the final syllable of a phrase is “a special musical characteristic […] independent of the linguistic tones of the text” (Yung 1983, 36). Therefore, in end-of-phrase melismas, I will take the first pitch as the mapping locus, since 33 the subsequent notes are merely ornamental elaborations. In Figure 9 below, which shows a phrase taken from the last verse of “七友 (cat1 jau5)” (C0301), the final syllable “口 (hau2)” is sung over a three-note (D4–C4–B♭4) melisma. In this case, since this melisma takes place at the end of the phrase, the first pitch D4 will serve as the mapping locus for the syllable “口 (hau2)”. Accordingly, the final bigram of the phrase would comprise the pairs of pitches E♭4–D4 from the syllables “傷 (soeng1)” and “口 (hau2)” respectively. Figure 9. An excerpt from the last chorus of “七友 (cat1 jau5)” (C0301) An exception to the case of end-of-phrase melisma is when the first note of an end-of-phrase melisma is an embellishing tone. In those cases, the mapping locus will be the first structural pitch in the melisma. For example, in Figure 10, the mapping locus for the syllable “忍 (jan2)” is the second pitch in the melisma (C♯4). Below the transcription of this excerpt, I have provided a Roman Numeral analysis of the four measures in the excerpt. Given the ii harmony on which the melismatic syllable “忍 (jan2)” is sung, the first chord tone in the melisma is C♯4, whereas the D♯4 that precedes it serves as an appoggiatura. In this case, the first pitch in the melisma acts as an embellishing tone that should not be chosen as the mapping locus. Since the C♯4 is the first structural pitch in the melisma, it should thus be chosen as the mapping locus. In my transcription, embellishing pitches like the D♯4 appoggiatura in this example are encoded as grace notes and will be skipped over in my computation. Figure 10. An excerpt from the second chorus of “重新長大 (cung4 san1 zoeng2 daai6)” (C1205) 34 The last category of melismatic syllables contains those that fall into neither of the above types. In these cases, I will identify the mapping locus by analyzing the relevant passage and selecting the first structural pitch within the melisma. To illustrate this process, in Figure 11 below I present an excerpt from “無賴 (mou4 lai2)” (C0503). The second phrase of this excerpt begins on the syllable “口 (hau2)” which is set melismatically to two pitches, D♯4 and C♯4. This instance of a melismatic syllable belongs to neither the portamento type nor the end-of-phrase type, since it does not anticipate the pitch of the next syllable nor occur at the end of a phrase. Therefore, in order to select a pitch as the mapping locus for this syllable, I consider the relative structural importance of the two pitches presented in this melisma. The first measure—the one in which the melismatic syllable is sung—has an underlying harmony of IV, with chord tones A, C♯, and E. Consequently, the first pitch of the melisma (D♯4) should be understood as a neighbour tone that embellishes the chord tones (C♯4) that come before and after it. In other words, the second pitch of the melisma (C♯4) carries greater structural importance and should be identified as the mapping locus for the syllable “口 (hau2).” Accordingly, the D♯4 that initiates the melisma will play no role in forming bigrams with neighboring syllables.24 Figure 11. An excerpt from the first chorus of “無賴 (mou4 lai2)” (C0505) 24 Studies on Anglophone popular music have revealed that there is a tendency for the vocal melody and the underlying harmony to be independent from each other. This phenomenon is commonly known as “melodic-harmonic divorce” as coined by Temperley (2007). The presence of melodic-harmonic divorce might complicate the identification of the structural tone in melismas. Nonetheless, based on my impression during the transcription process, melody and harmony in Cantopop seem to be closely connected and not “divorced” in Temperley’s sense. For example, in the example in Figure 11, most melodic pitches are chord tones and the treatment (or resolution) of non-chord tones follows the voice-leading conventions expected for common non-chord tone categories like neighbor tones. 35 In sum, Figure 12 below summarizes the criteria for selecting the mapping locus within a melisma. In my transcriptions, pitches that are not mapping loci will be flagged with a marker. When I employ the Humdrum toolkit to extract bigram data from the corpus, the commands will only consider the mapping loci in the computation. Figure 12. Decision tree for selecting mapping locus within a melisma 36 4. The Problem of Contour Tones 4.1. Contour tones and the endpoint principle As mentioned in Section 2.2, the text-setting constraint for tone languages manifests itself primarily through directionality—that is, first and foremost, the avoidance of contrary motion formed by speech and song melodies. This constraint seems rather straightforward, except for cases of where contour tones (T2 [25] and T5 [23] in Cantonese) are present. Figure 13 below shows three bigrams comprising different combinations of level and contour tones in Cantonese. The bigram in Figure 13a consists of two level tones—T3 [33] and T6 [22]. Since level tones have the same pitch as the tonal onset and tonal target, the succession of level tones does not cause any ambiguity in determining the direction of speech melody. In this case, the motion from T3 [33] to T6 [22] can only be understood as a downward movement. Figure 13. Bigrams with level and contour tones However, the presence of contour tones in bigrams can complicate the determination of directionality. Figure 13b shows an example where T5 [23] is followed by T3 [33]. On the one hand, by pairing the tonal onset [2] of T5 [23] with T3 [33], the bigram demonstrates an upward movement (dashed arrow inFigure 13b). On the other hand, if directionality is determined using the tonal target [3] of T5 [23], there is a level movement between the tones (solid arrow in 37 Figure 13b). In Figure 13c, where both tones constituting the bigram are contour tones, there are even more theoretical possibilities for describing the directionality. The 2×2 combination of tonal onsets and tonal targets—as shown by the four arrows in Figure 13c—yields four theoretical possibilities for describing the speech melody, whereby upward, level, and downward movements are all plausible. Therefore, in order to study tone-melody correspondence in Cantonese, it is necessary to first determine a consistent way to describe directionality of bigrams when contour tones are present. Ladd (forthcoming) has described the handling of contour tones as one of the “problems in theories of tone-melody matching.” Earlier scholars have recognized how contour tones pose a problem in Cantonese text-setting. When Yung (1983) studied text-setting in Cantonese opera, he observed that syllables with a (rising) contour tone were often set melismatically to two pitches in the song melody, with the second pitch higher than the first. By reproducing the upward tone contour with ascending musical pitches, this treatment of contour tones constitutes parallel motion between speech and song melodies. Handling contour tones this way is possible in Cantonese opera, since melismatic text-setting is commonplace in the genre. The aria type Yung investigated in his 1983 study belongs to one of the more syllabic types, but there are nonetheless sufficient instances of melisma for him to observe how contour tones can be set melismatically to form parallel motion with the song melody (Yung 1983, 42). By contrast, text-setting in Cantopop is mostly syllabic. While early Cantopop from the 1950s and 1960s show strong influences from Cantonese opera, the old-fashioned text-setting method and singing style that were inherited from Cantonese operatic melodies—including the tendency to set words melismatically—failed to appeal to the younger generations (Chu 2017, 38–39). As a result, in the 1970s, Cantopop songwriters eschewed the melismatic tendency in Cantonese opera and adopted a more syllabic style instead (C. W. Wong 2020, 201). Since then, syllabic text-setting has become the norm in Cantopop, in contrast to melismatic arias and fixed tunes in Cantonese opera. For instance, in the 105 songs of my corpus, 97.20% of the syllables (36,815 out of 37,877) are set syllabically. In other words, the strategy of setting contour tones 38 melismatically in Cantonese opera does not apply in contemporary Cantopop, indicating that a different approach to text-setting is required. Therefore, when studying tone-melody correspondence in Cantopop with respect to directionality, one must first determine whether the tonal onset or the tonal target of a contour tone should be used as the principal pitch for mapping the speech melody, since there is often only one pitch in the song melody per syllable. The current consensus among Cantopop scholars is that it is tonal targets of contour tones that are relevant to the text-setting process, whereas tonal onsets and contours are irrelevant. This preference given to tonal targets in Cantonese text-setting is described as the “endpoint principle” by Ladd (forthcoming, 11) and was first proposed by Marjorie K. M. Chan (1987a; 1987b). For example, for a T5 [23]–T2 [25] bigram, (Figure 13c above), the directionality should be determined with regard to the tonal targets of each syllable (i.e., [3] and [5] respectively, along the solid arrow in the figure); the resulting conclusion would be that T5 [23]–T2 [25] constitute an upward movement in the speech melody. The endpoint principle is now adopted as the general assumption for scholars studying tone-melody correspondence in Cantonese. Most existing studies have started from the assumption of the endpoint principle and considered contour tones in bigrams accordingly (e.g., Wong and Diehl [2002], Chow [2012], Lo [2013], and Kirby [forthcoming]), only providing evidence in favor of the principle (e.g., see Ho [2006; 2010, 46–49] and Ladd [forthcoming, 12]). However, no studies to date have critically examined the validity of the endpoint principle in Cantopop. Therefore, it is time to consider other theoretical possibilities for describing directionality for bigrams with contour tones and review how the endpoint principle actually holds in empirical data of Cantopop. 4.2. Evaluating the endpoint principle In this section, I further examine the endpoint principle by focusing on the argument from which the principle emerged. I will elucidate the shortcoming in the evidence for the 39 endpoint principle, demonstrating the need to reexamine its validity. Then, I investigate the implication of the endpoint principle on Cantopop text-setting, the predictions it makes about empirical data from the genre, and whether those predictions hold in the current corpus. Marjorie K. M. Chan (1987a; 1987b) first formulated the endpoint principle categorically in her study of Cantopop. She examined instances where the same melody is set to different texts (e.g., different iterations of verses in a song) and compared tones in these different lines of text. When Ho (2006; 2010, 46–49) attempted to justify the principle later on, she employed the same methodology from Chan’s study. Figure 14 reproduces an example used by Ho to illustrate the endpoint principle (2006, 1417; 2010, 47). This example is taken from a Cantopop song “落花流水 (lok6 faa1 lau4 seoi2).” Figure 14. An excerpt of “落花流水 (lok6 faa1 lau4 seoi2)” reproduced from Ho (2006, fig. 10) In this example, two different lines of text (listed in separate rows beneath the staff notation, with romanization and Chao number for tones listed below each line) are set to the same melody. Tones that differ across the verses are underlined by Ho in the figure. According to Ho, since T1 [55] and T2 [25] are found at the same place in the melody (the fifth and seventh syllables in Figure 14), one could reason that T1 [55] and T2 [25] are treated as equivalent in Cantopop text-setting. Similarly, the same reasoning applies also to T3 [33] and T5 [23] (the sixth and eighth syllables in Figure 14). In other words, Chan and Ho both claim that since both level and contour tones of the same tonal target could be found in the same musical context, 40 only the register of the tonal target matters in tone-melody correspondence, and the different tonal onsets and the upward contour are irrelevant. However, Chan’s and Ho’s argumentation for the endpoint principle commits the fallacy of a slippery slope, meaning that the same argument could also lead to erroneous conclusions.25 Consequently, this line of reasoning is faulty and casts doubt on the validity of the endpoint principle. Figure 15 below shows an excerpt from the song “數你 (sou2 nei5),” which is used as another example in Ho’s (2010) dissertation. In this excerpt, two different lines of text are set to the same melody, just like the examples Chan and Ho used to illustrate the endpoint principle. Although Ho used this example to support another argument, it demonstrates a logical flaw in Chan’s and Ho’s argumentation for the endpoint principle. Figure 15. An excerpt of “數你 (sou2 nei5)” adapted from Ho (2010, ex. 4-14) On the one hand, by focusing on the third syllable in each line in Figure 15 (i.e., 點 dim [25] and 一 jat [55]), one could say that this observation supports the endpoint principle, similar to Ho’s example in Figure 14. On the other hand, if the same reasoning is applied to the fifth syllable in each line (i.e., 着 zoek [22] and 最 zeoi [33]), one would arrive at the conclusion that 25 In the following paragraphs, I adopt the analytical framework from Rizzo and Whitman (2003) for describing Chan’s and Ho’s argumentation as a slippery slope. In this framework, the key components of a slippery slope argument are: (1) “an initial, seemingly acceptable argument and decision;” (2) “a later argument and decision that are clearly unacceptable;” and (3) “a ‘process’ or ‘mechanism’ by which accepting the initial argument and making the initial decision raise the likelihood of accepting the later argument and making the later decision” (Rizzo and Whitman 2003, 544). 41 the mid-register level tone T3 [33] and the low-register level tone T6 [22] are treated as equivalent, since they are used in the same position of the same melody. However, this conclusion contradicts all existing studies on tone-melody correspondence, including Chan’s (1987a; 1987b) and Ho’s (2006; 2010), which argue that song melodies in Cantopop do preserve the registral distinction between T3 [33] and T6 [22]. Therefore, if we accept the endpoint principle based on Chan’s and Ho’s argumentation, we are led to also accept the erroneous conclusion about T3 [33] and T6 [22] being equivalent in Cantopop text-setting. The counterexample offered in Figure 15 shows that the reasoning behind the endpoint principle is flawed. The argument for the principle is contingent on the example that was arbitrarily picked by the researchers. By looking only at selected musical examples, one can make claims that are not generally true for text-setting in Cantopop. Consequently, since Chan’s and Ho’s evidence for the endpoint principle is based on flawed argumentation and biased sampling, there is a need to systematically reexamine whether the endpoint principle truly holds in Cantopop. A recent study by Ladd (forthcoming) has attempted to do so but this follow-up still invites reexamination. Using the eight-song corpus compiled by Kirby (forthcoming), Ladd tested the validity of the endpoint principle by comparing “bigrams consisting only of level tones with bigrams involving contour tones” (forthcoming, 12). Ladd’s argument is that “if the endpoint principle is correct, there should be no quantitative difference between the two types of bigram” (forthcoming, 12). That is to say, the endpoint principle hypothesizes that, for a bigram type with level tones (e.g., T1 [55]–T1 [55]), if the corresponding song melody shows a certain distribution of downward, level, and upward movement, then the same distribution should also be observed for the bigram type with contour tones that have the same tonal target (e.g., T2 [25]–T2 [25]). In Table 8 below I reproduce the data extracted by Ladd (forthcoming, Table 4), showing the count of bigrams with mid-register level and contour tones (i.e., T3 [33] and T5 [23] respectively), classified according to the directionality of song melody. 42 Table 8. Count of bigrams with T3 [33] and T5 [23], adapted from Ladd (forthcoming, Table 4) Direction of song melody (contrapuntal motion) Bigrams with mid-register tones Downward (Oblique II) Upward (Oblique II) Level (Similar) Total T3 [33]–T3 [33] 4 (7.14%) 6 (10.71%) 46 (82.14%) 56 (100%) T5 [23]–T3 [33] 3 (8.82%) 12 (35.29%) 19 (55.88%) 34 (100%) T3 [33]–T5 [23] 6 (14.29%) 9 (21.43%) 27 (64.29%) 42 (100%) T5 [23]–T5 [33] 3 (16.67%) 1 (5.56%) 14 (77.78%) 18 (100%) The first row in Table 8 shows that 46 out of 56 (82.14%) of T3 [33]–T3 [33] bigrams comprise a level song melody, thus constituting similar motion between speech melody and song melody. Given this observation, the endpoint principle would predict that bigram types with other combinations of mid-register tones would have a distribution that is comparable to that of the T3 [33]–T3 [33] type, since the presence of tone contour should have no relevance for Cantopop text-setting. A closer look at Table 8 would reveal that this is not true; bigram types with contour tones (i.e., all data rows except for T3 [33]–T3 [33]) are less frequently set to a level song melody, when compared with the 82.14% count for T3 [33]–T3 [33] bigrams. A Fisher exact test was performed to determine whether this difference in the proportion of level song melody is statistically significant.26 The test reveals that this difference is statistically significant (p = 0.041),27 indicating that the distribution of directionality of song melody and the presence of contour are dependent on each other. Therefore, Ladd’s data casts doubt on the endpoint principle. Ladd was aware of the difference shown in Table 8, but he did not use statistical tests to verify the significance of this difference. He argued that the reported percentages “appear 26 The Fisher exact test is a statistical test used to test whether two categorical variables are associated or independent. It is an alternative to the chi-squared test when sample sizes are small. For more information about the Fisher exact test, see Sprent (2010). In this study, I have performed all statistical tests with SPSS. 27 The threshold for statistical significance is taken to be 0.05 throughout this study. 43 roughly comparable” across the rows (which is disagreed by statistical evidence) and that this data nonetheless do not challenge the “clear evidence for the validity of the endpoint principle” (Ladd, forthcoming, 12). He defended his argument by claiming that the lower percentages of similar motion for bigrams with contour tones “may involve special cases,” and that they do not challenge “the broad validity” of the endpoint principle (Ladd, forthcoming, 13). Nonetheless, Ladd did not offer a coherent explanation as to what linguistic or musical properties contributed to these “special cases.” Consequently, there is a need to reevaluate this difference in text-setting for bigrams with level tones versus contour tones and to modify the endpoint principle, which seems to oversimplify the role of tone contours in Cantopop text-setting. In addition to statistical evidence that challenges the endpoint principle, Ladd’s argument for the endpoint principle also needs refinement because he only considered the directionality of the song melody, but not the size of melodic intervals. Previous research has shown that when lyricists write texts for Cantopop, directionality of the contrapuntal motion between speech and song melody is not the only concern; instead, setting bigrams to an appropriate melodic interval is also crucial for making the lyrics sound intelligible and unambiguous (Ho 2010; Chow 2012; C. W. Wong 2020; K. Y. Chan, forthcoming). Therefore, with empirical data extracted from Cantopop songs, it might be revealing to break down the count of each type of movement in the song melody and observe whether there is a difference between sizes of melodic intervals across the bigram types. For instance, for bigrams with an upward movement in the song melody, is the average interval size larger for bigrams with level tones than those with contour tones? If there is a significant difference between interval sizes for different bigram types, that would mean that the endpoint principle needs to be further modified in order to more accurately describe the text-setting practice for level versus contour tones. In sum, the current scholarly confidence in the endpoint principle is ill-founded: evidence from musical examples lacks logical strength, and quantitative data from Cantopop challenges the validity of the endpoint principle. Consequently, a more critical approach must 44 be taken to evaluate the endpoint principle, with stronger evidence from a larger and more representative sample. 4.3. Evidence from the Cantopop corpus With data extracted from my corpus, I reexamine the endpoint principle and reformulate how level tones and contour tones are treated in the text-setting process for Cantopop. In the following paragraphs, I will present the data from my corpus, focusing on level and contour tones in the high-register and the mid-register. (Low- and extra-low-register tones are irrelevant in this section since there are no contour tones in these two registers. See Section 2.1 for the classification of tones.) My data will offer directions for supplementing the endpoint principle in order for it to better describe the text-setting practice in Cantopop. 4.3.1. Data on high-register tones (level T1 [55] and contour T2 [25]) In my corpus, there are 5,696 bigrams that consist of a pair of high-register tones: T1[55]–T1[55], T1[55]–T2[25], T2[25]–T1[55], or T2[25]–T2[25]. A breakdown of counts for each bigram type is listed in Table 9. Table 9. Count of each bigram type with high-register tones Bigram type T1 [55]–T1 [55] T1 [55]–T2 [25] T2 [25]–T1 [55] T2 [25]–T2 [25] Count 2,723 1,269 1,201 503 As mentioned in Section 4.2, the endpoint principle hypothesizes that if the bigram type with only level tones (i.e., T1 [55]–T1 [55]) shows a certain distribution for the direction of the corresponding song melody, then the same distribution should also be observed for bigram types with contour tone T2 [25], which has the same tonal target as T1 [55]. Among the 2,723 T1 [55]–T1 [55] bigrams in my corpus, 53.10% of them have a downward song melody and 3.05% an upward one. For these bigrams, since the musical pitch is changing while the tone is unchanged, this constitutes oblique motion (type II) between speech and song melody. The 45 remaining 43.85% show similar motion, since they are set to two identical pitches successively—that is, a level song melody. This distribution is presented as a pie chart in Figure 16. Figure 16. Distribution of song melody for T1–T1 [55] bigrams If the endpoint principle is valid, then the distribution in Figure 16 would be what one expects to see for other bigram types with high-register tones in the corpus. With that expectation in mind, one can examine the data for bigrams with the high-register contour tone T2 [25] and see how they compare with this prediction made by the endpoint principle. Figure 17 below shows the proportions of downward, level, and upward song melodies for each bigram type with a pair of high-register tones. It demonstrates several remarkable ways in which the data for bigrams with contour tones (i.e., T1 [55]–T2 [25], T2 [25]–T1 [55], and T2 [25]–T2 [25]) differ from the distribution for T1 [55]–T1 [55] bigrams. First, for T1 [55]–T2 [25] bigrams (orange bars in Figure 17), a much lower proportion (35.46%) of them are set to a level song melody, in contrast to 43.85% for T1 [55]–T1 [55] bigrams. At the same time, comparing with T1 [55]–T1 [55] bigrams, T1 [55]–T2 [25] bigrams are more likely to be set to a downward song melody (62.17% versus 53.10%)—that is, an oblique motion. A Fisher’s exact test reveals that the difference in song melody distribution between T1 [55]–T1 [55] and T1 [55]–T2 [25] 46 bigrams is statistically significant (p < 0.001). Therefore, quantitative evidence supports the observation that T1 [55]–T2 [25] bigrams are less likely to be set in similar motion and more likely in oblique motion with a downward song melody. Figure 17. Distribution of song melody for bigrams with a pair of high-register tones Second, compared with T1 [55]–T1 [55] bigrams, T2 [25]–T1 [55] bigrams (grey bars in Figure 17) are less commonly set to a downward song melody (46.79% vs. 53.10%) and more commonly to an upward one (10.66% vs. 3.09%). Notably, an upward song melody is rare for other bigram types with high-register tones; only with T2 [25]–T1 [55] bigrams can one observe a higher proportion of upward song melody. Statistical evidence from a Fisher’s test shows that these differences in the direction of song melody between T1 [55]–T1 [55] and T2 [25]–T1 [55] bigrams are significant (p < 0.001). This implies that the rising contour of T2 [25] tone sets the tone apart from T1 [55] in terms of text-setting strategies; bigrams involving T2 [25] is being treated differently from those with only T1 [55]. In sum, by contrasting the data for T1 [55]–T1 [55] bigrams with those for T1 [55]–T2 [25] and T2 [25]–T1 [55], one can see that empirical data from my corpus brings the endpoint principle into question, since the distribution of song melody is different for bigrams with 53.10%43.85%3.05%62.17%35.46%2.36%46.79%42.55%10.66%52.68%43.34%3.98%0%10%20%30%40%50%60%70%Down Level UpT1–T1 T1–T2 T2–T1 T2–T2 47 contour tones and those with only level tones. Although the proportions of directionality might be roughly similar across the bigram types, there are subtle yet significant differences between bigrams with and without contour tones. For high-register bigrams with contour tones, similar motion is less common than high-register bigrams with only level tones, whereas oblique motion is more common. In addition, for T2 [25]–T1 [55] bigrams, the presence of a rising tone contour seems to justify the use of an upward song melody, which is rare for bigrams with only level tones.28 4.3.2. Data on mid-register tones (level T3 [33] and contour T5 [23]) In the previous section, I have described how my corpus data about high-register tones pose questions about the endpoint principle. In this section, I will use the same process as above to demonstrate how my data on mid-register tones (T3 [33] and T5 [23]) support the same conclusion. A breakdown of counts for each bigram type with mid-register tones is listed in Table 10. Table 10. Count of each bigram type with mid-register tones Bigram type T3 [33]–T3 [33] T3 [33]–T5 [23] T5 [23]–T3 [33] T5 [23]–T5 [23] Count 886 559 635 503 To determine whether the endpoint principle holds for mid-register contour tones, I examine song melodies for bigrams with only the mid-register level tone T3 [33]—that is, the T3 [33]–T3 [33] type. As Figure 18 shows, most (81.26%) T3 [33]–T3 [33] bigrams are set to a level song melody, demonstrating similar motion between speech and song melody. The proportion for downward and upward song melodies are 4.85% and 13.88% respectively. 28 No statistically significant difference exists between the distributions of song melody for T1 [55]–T1 [55] and T2 [25]–T2 [25] bigrams according to the results of a Fisher’s test (p = 0.532). In addition, for each bigram type, I computed the mean of interval sizes for downward and upward movements in the song melodies respectively. Using an independent samples t-test, I found no statistically significant difference between these mean interval sizes for each direction across bigram types. 48 Figure 18. Distribution of song melody for T3 [33]–T3 [33] bigrams Then, the distribution for T3 [33]–T3 [33] bigrams can be compared with bigram types that involve the contour tone T5 [23] (i.e., T3 [33]–T5 [23], T5 [23]–T3 [33], and T5 [23]–T5 [23]), as listed in Figure 19 below. Recall that for high-register tones, bigrams with contour tones are more likely to be set to oblique motion. The same can also be observed for mid-register tones, with a propensity for an upward song melody. As Figure 19 demonstrates, for all bigram types with contour tone T5 [23], the proportion of song melodies with a level movement is lower than the 81.26% count for T3 [33]–T3 [33]. At the same time, they are more commonly (ranging from 18.96% to 20.81%) set to an upward song melody, compared with 13.88% for T3 [33]–T3 [33]. Results of Fisher tests reveal a significant difference between the distribution for T3 [33]–T3 [33] and that for each bigram type involving T5 [23] (i.e., T3 [33]–T3 [33] vs. T3 [33]–T5 [23], T3 [33]–T3 [33] vs. T5 [23]–T3 [33], and T3 [33]–T3 [33] vs. T5 [23]–T5 [23] respectively). This suggests there is a connection between the different distribution of song melody directions and the presence of contour tone in the bigrams. 49 Figure 19. Distribution of song melody for bigrams with a pair of mid-register tones Nonetheless, as shown in the data above, when level and contour tones in the mid-register (i.e., T3 [33] and T5 [23]) appear successively in Cantopop, level movement is still the most common type of movement for the song melodies. This means that the endpoint principle is partially right about tonal targets being a relevant reference point with which one can assign pitch register to the contour tones. However, there is indeed some difference in the text-setting of contour tones in comparison with their level counterpart. In sum, studying level and contour tones in this corpus has revealed the inadequacy and oversimplicity of the endpoint principle, which has failed to capture the subtle yet significant effects of tone contours on the directionality of song melody in Cantopop. Therefore, there is a need to supplement the endpoint principle by describing how tone contours contribute to the differences observed above. 4.4. Discussion The previous section has presented evidence on how bigrams with contour tones are more likely to be set to oblique motion, compared to those bigrams with only level tones. 4.85%81.26%13.88%2.15%78.89%18.96%6.77%74.02%19.21%0.85%78.34%20.81%0%10%20%30%40%50%60%70%80%90%Down Level UpT3–T3 T3–T5 T5–T3 T5–T5 50 Consequently, the endpoint principle must be modified: level and contour tones in the same register are not treated as equivalent and interchangeable in Cantopop text-setting. Instead, the presence of contour tones justifies the more common use of oblique motion in same-register bigrams, in contrast to bigrams with only level tones. In this section, I offer possible explanations for this tendency for contour tone bigrams to be set to oblique motion. Recall that linguists have described the text-setting constraint for tone languages as a three-tier system of preferences (see Section 2.2): first and foremost, contrary motion is strongly avoided; second, oblique motion is weakly avoided; and third, similar motion is preferred. For bigrams with same-register tones examined in Section 4.3, contrary motion is not a possibility. This is because contrary motion comprises the pairing of upward and downward movements in the speech and song melodies, whereas the movement in the speech melody must be level when both tones are in the same register. As a result, given the level speech melody, bigrams with same-register tones can only be set in oblique motion (type II) or similar motion. In keeping with the text-setting constraint principle, oblique motion should be avoided and similar motion preferred. In other words, one can understand the tendency for contour tone bigrams to be set to oblique motion as the relaxation of the text-setting constraint for contour tones. Since the text-setting constraint for tone languages serves to maintain intelligibility and unambiguity of song lyrics, the relaxed text-setting constraint for contour tones would mean that intelligibility of the lyrics could be comprised. Therefore, for this relaxation to be allowed in Cantopop text-setting, there should be additional cues that compensate for this potential loss of intelligibility and allow listeners to correctly understand the words, so that the meaning of the text would remain intelligible even though the speech and song melodies go in oblique instead of similar directions. To supplement the widespread assumption of the endpoint principle and explain why the text-setting constraint is relaxed for contour tones, I propose that the pitch profile of contour tones contributes additional perceptual cues that ensure correct understanding of lyrics. In Cantonese singing, contour tones are realized by adding an upward microtonal glide at the 51 beginning of the syllable before reaching the target pitch in the song melody, and this is true even for Cantonese speakers without professional vocal training (Schellenberg and Gick 2020). Figure 20. Vocal pitch contour of the first eight syllables in “世上只有 (sai3 soeng6 zi2 jau5)” (C0405) To demonstrate this glide in Cantopop singing, Figure 20 plots the vocal pitch contour of the first eight syllables in a song in my corpus “世上只有 (sai3 soeng6 zi2 jau5)” (C0405); the pitch contour is shown by the blue line. I extracted the vocal line from the recording using Moises, an application for track separation, and created the plot using the speech processing software Praat.29 Orange dotted lines in the graph indicate the onset of each syllable, with the corresponding word and its romanization and tone listed above. In these two phrases, there are four syllables that carry a contour tone (T2 [25] or T5 [23]), as indicated with boldface and underline. Green boxes spotlight the upward glide that precedes the main pitch on which the syllable is sung; although each word is sung syllabically, the singer adds the glide to represent the tone contour. Therefore, with the glide present, the listener would know that the tone of the syllables could only be T2 [25] or T5 [23] (hence with only two registers possible).30 29 Moises and Praat can be accessed at https://moises.ai/ and https://www.fon.hum.uva.nl/praat/ respectively. 30 It is interesting that the singer added an upward glide to the initial syllable “望 (mong6)” in the line. Since this syllable has a level tone (T6 [22]), this glide is not a result of realizing linguistic tones in singing. This glide might be relevant to some other aspects of the vocal performance. 52 Table 11. Frequency distribution of the six Cantonese tones in Cantonese speech and Cantopop corpora Tone Frequency and percentage in speech corpus (Leung, Law, and Fung 2004) Frequency and percentage in Cantopop corpus T1 [55] 30,145 21.36% 8,734 23.06% T2 [25] 23,346 16.54% 4,329 11.43% T3 [33] 27,002 19.13% 6,738 17.79% T4 [11] 15,898 11.26% 5,509 14.54% T5 [23] 15,098 10.70% 5,073 13.39% T6 [22] 29,660 21.01% 7,494 19.70% Total 141,149 100.00% 37,877 100.00% A study on a Cantonese speech corpus reveals that contour tones are relatively uncommon in Cantonese speech when compared with level tones (Leung, Law, and Fung 2004). As illustrated in Table 11 above, among the 141,149 syllables sampled in the speech corpus, 23,346 of them are in T2 [25] and 15,098 are in T5 [23]. In other words, syllables with contour tones account for less than 30% of the syllables in the speech corpus. In addition, the frequency of each contour tone is also lower than their level counterpart—that is, there are fewer syllables with high-register contour T2 [25] than level T1 [55] (highlighted in blue in Table 11), and fewer syllables with mid-register contour T5 [23] than level T3 [33] (highlighted in green in Table 11). Table 11 also reports the frequency of each tone in my Cantopop corpus, and the data from the Cantopop corpus show the same pattern as the speech corpus and support the observation that contour tones are rarer than level tones. When Cantopop singers add an upward glide in a sung syllable, the listener would then understand that the sung syllable should have a contour tone. Consequently, the presence of the glide would assist the listener in correctly understanding the word, simply by reducing the number of minimal pairs with the given consonants and vowels.31 As a result, the text-setting 31 Minimal pair is “a pair of words distinguished by a single phoneme” (P. H. Matthews 2014), such as consonant, vowel, or tone. An example of a tonal minimal pair in Cantonese would be 梳 (so1, meaning 53 constraint can be relaxed for contour tones, since the presence of the upward glide can serve as a perceptual cue that aids listeners in correctly understanding the lyrics, despite the oblique motion (rather than similar) between speech and song melodies. In the following paragraphs, I will provide musical examples to illustrate how contour tones may be set more flexibly in Cantopop. By taking examples from songs included in my corpus, I will discuss the setting of contour tones in the songs and support my claim about how the text-setting constraint can be relaxed for bigrams with contour tones. Figure 21. An excerpt from the first verse of “烈女 (lit6 neoi2)” (C0504) Figure 21 above shows the transcription on a phrase from the song “烈女 (lit6 neoi2)” (C0504) in my Cantopop corpus. In this phrase, the final notes F♯4 and E4 form a descending major second, which is set in an oblique manner to the words “恭喜 (gung1 hei2).” Both syllables in this bigram are high-register tones, with the first “gung” carrying a level tone T1 [55] and the second “hei” a contour tone T2 [25]. In Cantonese, there is no word for the syllable “hei” with a contour tone T5 [23], even though this sound exists in theory (Multi-function Chinese Character Database, 2018). Accordingly, a sung syllable “hei” with an initiatory upward glide can only be heard as having the contour tone T2 [25], regardless of the motion of the song melody leading to this syllable. In this case, although two tones of the same register are set to oblique (type II) instead of similar motion, the relaxation of the text-setting constraint does not compromise the intelligibility of the lyrics. This is because the room for misinterpretation is eliminated by the non-existence of the pairing between the “hei” syllable “comb”) and鎖 (so2, meaning “lock”). These two words have the same combination of consonants and vowels and differ only in tone (T1 vs T2). 54 and the contour tone T5 [23]. In general, since contour tones are relatively rare in the phonological inventory of Cantonese, this rarity allows for a relaxed text-setting constraint for setting contour tones in Cantopop. Figure 22. An excerpt from the second verse of “烈女 (lit6 neoi2)” (C0504) The second iteration of the same phrase in the second verse of the song is shown in Figure 22. In this version of the phrase, the final bigram comprising pitches F♯4 and E4 is not set to T1 [55] and T2 [25] respectively as in the first verse (Figure 21), but the second syllable is set to T3 [33] instead. In other words, in this instance, the descending song melody is set to a speech melody that is also descending, thus constituting a similar motion. As discussed in Section 4.2, Marjorie K. M. Chan’s endpoint principle (1987a; 1987b) suggested that level and contour tones with the same tonal target should be treated as equivalent in Cantopop text-setting. But as shown in the comparison between Figure 21 and Figure 22, the syllable with T2 [25] in verse 1 is replaced by T3 [33] in the second iteration of the verse. According to Chan’s endpoint principle, T3 [33] should not be expected to take the place of T2 [25] in an identical musical context, since T2 [25] and T3 [33] have different tonal targets. Instead, according to the endpoint principle, T1 [55] would be an appropriate option for taking the place of T2 in the same position of the phrase (see Section 4.2 for the underlying argumentation). The example shown in Figure 22 supports my claim about the relaxation of the text-setting constraint for contour tones because it demonstrates how the presence of tone contour would permit the occurrence of oblique motion, which constitutes a weak form of violation of the text-setting constraint. To contextualize this point, I return to the data extracted from my corpus. In Figure 23 below I present the distribution of speech melody for bigrams with a 55 descending major second, the final melodic interval in the examples in Figures 21 and 22. More than two thirds (67.69%) of bigrams with a descending major second are set in similar motion—that is, with a downward speech melody. These instances represent cases where the text-setting constraint is observed most strictly. Cases of oblique motion where the speech melody stays level while the song melody descends by a major second are less common, accounting for 31.89% (or 1,914) of the total. Therefore, the use of a T1 [55]–T2 [25] bigram—a level speech melody—in the descending second in the first verse of “烈女 (lit6 neoi2)” indicates that contour tones are treated not as equivalent to their level counterparts, but with an extra flexibility granted by the upward glide that is realized by the singer and not captured in transcriptions. Figure 23. Distribution of speech melody for bigrams with a descending major second Figure 24 presents an example from “我們都是這樣長大的 (ngo5 mun4 dou1 si6 ze2 jeong6 zoeng2 daai6 dik1),” another song in my Cantopop corpus, illustrating another instance where a bigram involving contour tones is set in an oblique manner. In this case, both tones in the bigram are the mid-register contour tone T5 [23]. As reported in Figure 19, for T5 [23]–T5 [23] bigrams, oblique motion with upward movement in the song melody is more common than its level tone counterpart (i.e., T3 [33]–T3 [33]). For T5 [23]–T5 [23] bigrams, 20.38% of them 56 are set across an ascending major second, whereas the percentage is only 12.75% for T3 [33]–T3 [33] bigrams. Figure 24. An excerpt from the final chorus of “我們都是這樣長大的 (ngo5 mun4 dou1 si6 ze2 jeong6 zoeng2 daai6 dik1)” (C1502) Figure 25. Vocal pitch contour of an excerpt from the final chorus of “我們都是這樣長大的 (ngo5 mun4 dou1 si6 ze2 jeong6 zoeng2 daai6 dik1)” (C1502) For the example in Figure 24, since both syllables of “wing5 jyun5” carry the contour tone T5 [23], the singer approaches each of them with an upward glide. The vocal pitch contour of this excerpt is plotted in Figure 25, showing the upward glides for the two T5 [23] syllables. This additional cue precludes most other plausible tone combinations when listeners are discerning the words. For example, without the glide, the melodic contour could lead the listener to perceive the syllables in tones T4 [11]–T6 [22], which is indeed the most common (26.27%) setting for bigrams with ascending major seconds. More importantly, this alternative 57 interpretation would also be semantically valid: with those tones, “wing4 jyun6” could be understood as “榮願,” translating as “the greatest wish.” Thus, the resulting phrase “榮願不變” could be misunderstood as “the greatest wish unchanging” if the syllables were not sung with the upward glide. In short, since singers supply the additional cue of the upward glide when singing contour-tone syllables, the risk of misunderstanding or unintelligibility is reduced for Cantonese listeners, and thus, lyricists can set contour-tone syllables more flexibly. In the above paragraphs I have explained how the perceptual cue of upward glides could lead to the relaxation of the text-setting constraint for contour tones, which is reflected by the tendency for bigrams with contour tones to be set in oblique motion, as my corpus data have revealed. In addition, I wish to also point out phonological changes in Cantonese tones that may contribute to this treatment of contour tones in Cantopop text-setting. Recent phonological studies on Cantonese have suggested that there seems to be an in-progress tone merger between T2 [25] and T5 [23] (Bauer, Cheung, and Cheung 2003; Peng 2006; R. S. Y. Fung and Lee 2019). Tone merger refers to “the collapse of the phonetic contrast of two tones” (R. S. Y. Fung and Lee 2019, EL424). Accordingly, a tone merger between T2 [25] and T5 [23] in Cantonese means that Cantonese speakers are tending to speak and perceive the pitch profiles of the two tones with less distinction, to an extent that these tone categories could become indistinguishable. If the tone categories of high-register T2 [25] and mid-register T5 [23] are merging as phonological studies have suggested, then one might understand T2 [25] as having a slightly lower pitch register than its level counterpart T1 [55], and T5 [23] as having a higher pitch register than its level counterpart T3 [33]. In other words, despite the schematic categorization of tone register based on Chao numbers, the pitch of T2 [25] and T5 [23] might be converging towards some kind of a mid-high register. The tone merger between T2 [25] and T5 [23] may explain why these contour tones are set differently from their level counterparts (i.e., T1 [55] and T3 [33], respectively). Recall that for high-register bigrams in my corpus, T1 [55]–T2 [25] bigrams are more likely to be set to a 58 downward movement in the song melody than T1 [55]–T1 [55] bigrams, whereas T2 [25]–T1 [55] bigrams are more likely to set to an upward movement in the song melody than other high-register bigrams (see Figure 17). The tone merger between T2 [25] and T5 [23] would explain these differences, since the pitch register of T2 [25] would be somewhat lower than T1 [55] if T2 [25] converges towards mid-register T5 [23]. Similarly, if T5 [23] is to be understood as having a higher register than its level counterpart T3 [33], then the tone merger can explain why a higher proportion of T5 [23]–T3 [33] bigrams are set to a downward song melody than T3 [33]–T3 [33] bigrams, and why a higher proportion of T3 [33]–T5 [23] bigrams are set to an upward song melody. While this corpus study can offer some preliminary evidence of the tone merger affecting tone-melody correspondence in Cantopop, a more specific investigation is needed. For instance, a follow-up inquiry with perceptual tests using carefully chosen stimuli and analysis of acoustical data from Cantonese speech and singing can more rigorously examine the effect of tone merger on the treatment of contour tones in Cantopop text-setting. In this chapter, I have critically evaluated the endpoint principle, the widespread assumption on which scholars have approached contour tones when studying tone-melody correspondence in Cantopop. Although the endpoint principle might be helpful as a prescriptive guide for one to “determine pitch direction across bigrams that include contour tones” (Ladd, forthcoming, 9), I have discussed how my Cantopop corpus offers evidence that the current understanding of the endpoint principle is inadequate and requires refinement. By showing that oblique motion is more common for bigrams with contour tones than for their level counterparts, I propose that upward glides in Cantopop singing serve as additional perceptual cues that aid listeners in accurately understanding the lyrics, so that the text-setting constraint may be relaxed for contour tones. Also, I have demonstrated the potential connection between Cantonese tone merger and the relaxed text-setting constraint for contour tones. In conclusion, this chapter has offered a supplement to the endpoint principle and has demonstrated the intricacy of Cantopop text-setting regarding contour tones. 59 5. Theoretical Issues about Oblique Motion In this chapter, I focus on two theoretical issues surrounding the setting of oblique motion in Cantopop—that is, when one of speech and song melodies is moving while the other stays level. The first concerns the two types of oblique motions—types I and II. Oblique I motion describes cases where the song melody stays level and the speech melody moves upward or downward, whereas oblique II motion refers to cases where the speech melody stays level and the song melody moves upward or downward (see Table 3). Oblique I motion is a rare occurrence in Cantopop, and for this reason its relation with the text-setting constraint has not been clearly understood. In this study, I propose that the understanding of oblique I motion should be informed by the text-setting process of Cantopop. The rarity of oblique I motion can be coherently understood if one describes the text-setting constraint separately for level and moving song melodies. The second theoretical issue concerns the directionality of oblique II motion, the more common type of oblique motion in Cantopop. Previous scholars have observed that T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams tend to have song melodies that go upward and downward respectively. I reexamine this claim by also considering the effect of pitch range—that is, the correlation between the starting pitch of a bigram in relation to the song’s pitch and the direction of the song melody. 5.1. The frequency of oblique I vs. oblique II motion As mentioned in Chapter 2, linguists have described the text-setting constraint for tone languages with respect to the three types of contrapuntal motion between speech and song melodies: contrary, oblique, and similar motion. The general understanding about the text-setting constraint is that contrary motion is more strongly avoided than oblique motion, whereas similar motion is the most preferred type of motion for maintaining tone-melody correspondence. However, this tripartite framework has recently been criticized for conflating 60 types I and II of oblique motion into one independent and coherent category (Ladd, forthcoming). Based on data from previous research on Cantopop (Lo 2013; Kirby, forthcoming), Ladd (forthcoming) argues there is a need to differentiate between types I and II of oblique motion when describing the text-setting constraint for the genre. Table 12 summarizes data from previous quantitative studies of Cantopop, showing the proportion of each type of contrapuntal motion. These data show that, while oblique II motion is rather common in Cantopop, oblique I motion is rare—even more so than contrary motion. The earliest such study by P. C. M. Wong and Diehl (2002) reports that 6.05% of bigrams in their sample demonstrate oblique motion, all of which are of type II and none are of type I. Unfortunately, this statistic is based on an erroneous conflation of the tonal targets [1] and [2]. That is, Wong and Diehl considered both T4 [11] and T6 [22] to be low-register tones, even though these two tones have different tonal targets. Consequently, they classified Cantonese tones into only three—but not four—registers.32 Despite this conflation of tone registers, their statistics have been quoted in recent literature on cross-cultural comparison of tone-melody correspondence (e.g., Schellenberg [2012] and McPherson and Ryan [2018]). To correct this misconception, there was a need for an updated study that recognizes the four distinct levels of tonal targets of Cantonese tones. Table 12. Proportion of contrapuntal motions in previous quantitative studies on Cantopop Study Number of songs Number of bigrams Proportion of contrapuntal motion Similar Oblique I Oblique II Contrary P. C. M. Wong and Diehl (2002) 4 281 91.81% 0% 6.05% 2.14% Lo (2013) 11 2,665 82.66% 2.29% 11.74% 3.30% Kirby (forthcoming) 8 1,720 77.33% 3.26% 14.53% 4.88% 32 This consequential oversimplification was also explicitly identified by Lo (2013) and Ladd (forthcoming). See Section 2.1 about the four-register classification of Cantonese tones. 61 Lo (2013) and Kirby (forthcoming) attempted to more accurately calculate the proportion of contrapuntal motions between speech and song melodies in Cantopop. Both used the four-register categorization of Cantonese tones and extracted data from slightly larger corpora of songs. Lo and Kirby reported 11.74% and 14.53% as the proportion of oblique II motion in their respective data, higher than the 6.05% figure given by Wong and Diehl.33 Although there are minor differences between the data reported by Lo and Kirby respectively, their results indicate that oblique II motion is commonplace in Cantopop. Indeed, some research has reported that oblique II motion is an important text-setting strategy for maintaining tone-melody correspondence in other tone languages, such as Duna (Sollis 2010), Kalam Kohistani (Baart 2004), and Vietnamese (Kirby and Ladd 2016). Therefore, Lo’s and Kirby’s data put Cantonese (or at least Cantopop) among these other languages in which oblique II motion is an important text-setting strategy. Nonetheless, there seems to be a crucial distinction between types I and II of oblique motion—that is, whether it is the song melody or the speech melody that is staying level in a bigram. From the statistics reported in Table 12, one can see that type II of oblique motion is always more prevalent than type I across the three studies. In other words, it is much more common for a level speech melody to be set to a moving song melody than vice versa. Another notable observation about oblique I motion is that it occurs even less frequently than contrary settings. As shown in Table 12, in this corpus oblique I motion is consistently the least common type of contrapuntal motion. Ladd (forthcoming, 9) suggested this means “the category ‘oblique’ may be somewhat incoherent.” If the text-setting constraint manifests primarily in the avoidance of contrary motion, as Ladd suggested, “oblique settings should be preferable to contrary settings” (Ladd, forthcoming, 11), and it would be contradictory for the occurrence of contrary motion to outnumber that of oblique I motion. 33 Lo (2013, 22–24) also found that the three-register division that Wong and Diehl used would tend to overstate the proportion of oblique motion and understate that of similar motion. As a result, the true difference in the proportion of oblique motion would likely be even larger if Wong and Diehl used the four-register division. 62 In short, empirical data has revealed that the current understanding about oblique motion in tone-melody correspondence is inadequate. The rarity of oblique I motion in existing Cantopop corpora seems paradoxical as it contradicts the expectation that oblique motion should be preferable to contrary motion. By considering data from my larger corpus, I will address this paradox related to oblique I motion and offer a coherent explanation. Table 13 illustrates distribution of the different types of contrapuntal motion in my Cantopop corpus. Percentages indicate the proportion of contrapuntal motions in relation to the grand total of bigrams throughout the corpus. My corpus data agree with the proportions found in previous studies (see Table 12) and support Ladd’s suggestion that types I and II of oblique motion should be differentiated. Only 0.72% of all bigrams in my corpus show oblique I motion (shaded in yellow in Table 13), whereas the percentage for oblique II motion (shaded in green in Table 13) is much higher at 14.91%. As expected, there is a great difference between the frequencies of oblique I and oblique II motions in the corpus. Table 13. Proportion of contrapuntal motions in my Cantopop corpus In addition, oblique I motion occurs even less frequently than both types of contrary motion (shaded in red in Table 13), which together account for 0.97% of all bigrams in the corpus. Since oblique I motion is the type of contrapuntal motion that is most rarely used—even 63 more so than contrary motion—Ladd’s proposal to differentiate between oblique I and II motions is further validated. When Ladd discussed the rarity of oblique I motion in Cantopop, he attributed this phenomenon to “a strictly musical constraint that disfavours same-note sequences,” meaning that song melodies “that keep moving” should be preferable to those with repeated pitches (Ladd, forthcoming, 9). Since oblique I motion comprises a level song melody and a moving speech melody, this musical constraint would explain why oblique I motion is rarer than oblique II and contrary motions, which must involve a moving song melody by definition. If this constraint is true, the result of this constraint would be few instances in Cantopop melodies where a note is repeated from one syllable to the next. Figure 26. Distribution of interval sizes in the Cantopop corpus I test Ladd’s explanation of melodic constraint by counting the interval sizes in song melody of all bigrams in the Cantopop corpus, and the distribution is shown above as Figure 26. (Positive interval sizes refer to ascending song melodies, and negative ones to descending song melodies.) This chart indicates that the most common interval size in the corpus is zero 0%5%10%15%20%25%-12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14Percentage of occurrenceInterval size in song melody (number of semitones) 64 semitones—that is, a pair of repeated pitches in the song melody—followed by descending and ascending major seconds (two semitones). The frequency for other interval types decreases as the magnitude of interval sizes increases, resulting in the bell-shaped distribution shown in Figure 26. This distribution accords with a general and cross-cultural musical tendency which is known as “pitch proximity” (von Hippel 2000), meaning that musical melodies tend to be constructed predominantly with small pitch movements. Therefore, Ladd’s claim about the preference for moving song melody in Cantopop requires refinement: while the most common melodic motion is to move up or down by two semitones, a level song melody occurs regularly. On the other hand, Ladd’s claim about the preference for moving song melody might be partially right if one specifies the comparison as one between Cantopop and Anglophone popular music. In Figure 27 below, I reproduce Example 5.8 from Temperley’s The Musical Language of Rock (2018, 98). This graph offers a count of melodic intervals in his Rolling Stone corpus, which comprises 200 Anglophone rock songs from the 1950s through the 1990s. The distribution of the sizes of melodic interval in the Rolling Stone corpus is similar to that in my Cantopop corpus, with a bell-shaped distribution that peaks at the interval of zero semitones. However, while around 20% of melodic intervals measure zero semitones in the Cantopop corpus, the percentage is slightly above 30% for the Rolling Stone corpus. This means that moving song melodies are indeed more common in Cantopop than in Anglophone rock music.34 Nonetheless, this does not dispute the fact that pitch proximity is a valid generalization for Cantopop and that repeated melodic pitches are commonplace in the song melody. Consequently, there should be other reasons behind the rarity of oblique I motion and to support the distinction between types I and II of oblique motion. 34 Note that the Rolling Stone corpus consists of songs from the 1950s through the 1990s, whereas my Cantopop corpus comprises songs from 2000 to 2020. Consequently, it is possible that the difference in the distribution of melodic interval is influenced by the time period the corpora represent. 65 Figure 27. The distribution of melodic intervals in the Rolling Stone corpus (reproduced from Temperley [2018, 98]) By interpreting the distribution of contrapuntal motions in Cantopop differently (see Table 13), the paradoxical rarity of oblique I motion can be justified. Researchers studying tone-melody correspondence in Cantopop often overlook one aspect of Cantopop songwriting—that is, the standard practice that the song melody is usually written before the lyrics. For most instances (e.g., 100 out of the 105 songs in my corpus), the composer and the lyricist are different individuals, so the setting of lyrics would take place independently of and subsequently to the composition of the song melody. This practice is known as “先曲後詞” in Cantonese, sometimes translated as “music-first, words-later” (Chow 2012, 109).35 This sequence of writing the music before the text can have profound implications for Cantopop research; in this study, it affects how one should interpret data like those shown in Table 13 above. When Ladd (forthcoming) described the rarity of oblique I contrapuntal motion in the corpus data he reviewed, he compared the frequencies of oblique I motion and contrary motion 35 This procedure has been the norm for Cantopop songwriting since the 1970s. For detailed accounts on this procedure and its development, see J. S. Wong (2003, 100–103) and Chow (2012, 109–12). For discussions on the reversed procedure of “words-first, music-later” in Cantopop songwriting, see Tsui (2018, 57–66) and C. W. Wong (2020, 146–67). 66 by controlling for the direction of speech melody. He argued that when one restricts the comparison to cases where the speech melody goes upward (e.g., the leftmost data column in Table 13), oblique I motion is outnumbered by contrary motion (Ladd, forthcoming, 9). Similarly, he also made the same observation for cases where the speech melody goes downward (e.g., the rightmost data column in Table 13). This interpretation of the data assumes that the direction of the speech melody is a predetermined condition for which songwriters compose the song melody, which contradicts the “music-first, word-later” practice of Cantopop songwriting. Instead, it would be more meaningful to compare the frequency of contrapuntal motions by controlling for the direction of the song melody, since lyricists decide what words to write based on a given song melody that was written beforehand. Table 14 below is modified from Table 13, with percentages now indicating the proportions in relation to the row totals in the rightmost column, which show the total number of bigrams with song melodies in a given direction. When one controls for the direction of the song melody, it becomes apparent that it is illogical to compare the frequencies between oblique I motion and contrary motion or between the two types of oblique motions. By definition, oblique I motion can only occur when the song melody is level (see the second data row in Table 14). And when that is the case, the contrapuntal motion between the level song melody and the speech melody can only be similar (when the speech melody stays level too) or oblique I (when the speech melody moves upward or downward). Other categories of contrapuntal motion—contrary and oblique II motions—require a moving song melody. Therefore, the frequency of oblique I motion can only be meaningfully compared with that of similar motion for bigrams that involve a level song melody—that is, along the second data row in Table 14. 67 Table 14. Proportion of contrapuntal motions in my Cantopop corpus with row totals The percentages in Table 14 reveal that the paradoxical rarity of oblique I motion (see Table 13) is actually a misconstruction: the frequency of oblique I motion can only be meaningfully compared with that of similar motion with a song melody, and the resulting comparison is in accord with the text-setting constraint. As shown in the second data row in Table 14, for level song melodies, the most common contrapuntal motion is similar motion (i.e., with a level speech melody), which is in accord with the tripartite model of text-setting constraints. Similarly, given an upward- or downward-moving song melody (see the first and third data rows in Table 14), similar motion is the most common type of contrapuntal motion between song and speech melodies, followed by oblique motion, with contrary motion being the rarest case. This set of proportions is also consistent with the ordering of the text-setting constraint regarding the types of contrapuntal motion. More importantly, interpreting the data while controlling for the direction of song melody can explain the paradox of contrary motion outnumbering oblique I motion. As reported in Table 14, oblique I motion constitutes 3.65% of all bigrams with a level song melody, whereas contrary motion accounts for 1.83% and 0.57% of all bigrams with upward and downward song melodies respectively. This means that the frequency for oblique I motion 68 appeared to be the lowest in the interpretation shown in Table 13 not because it is truly rarer than contrary motion, but because the proportions of contrapuntal motions have been calculated using the wrong totals. By computing the proportions with reference to the relevant types of song melody, it becomes clear that oblique I motion appears more frequently than contrary motion. Based on these observations from Table 14, I fine-tune the descriptions of text-setting constraints for Cantopop by separating the cases of moving versus level song melodies. Figure 28. Text-setting constraints for level vs. moving song melodies As illustrated in Figure 28, I propose that one should understand the text-setting constraints for level song melodies and moving song melodies separately. For level song melodies, oblique II and contrary motions are logically impossible, and the only possibilities are similar and oblique I motions, which can be ranked according to the current understanding of the text-setting constraint. In the absence of contrary motion, oblique I motion is the contrapuntal motion that is most strongly avoided, while similar motion is preferred for maintaining tone-melody correspondence. On the other hand, for song melodies that move upward or downward, the only possible type of oblique motion is type II. The text-setting constraint then comprises the avoidance of contrary motion and the preference for similar motion at the extremes, and with oblique II motion assuming an in-between status. The fine-tuned model shows that oblique I motion cannot be directly compared to oblique II or contrary motion. Oblique I motion occurs in a strictly different context from that 69 for oblique II or contrary motions—that is, whether the song melody is level or moving. Therefore, researchers should not draw conclusions about tone-melody correspondence in Cantopop by directly comparing their frequencies. Instead, the comparison between frequencies of the types of contrapuntal motion should be drawn only for song melodies of a given direction. Ladd (forthcoming) is correct about the need to distinguish between oblique I and II motions, but this need does not arise from the comparison of their frequencies in relation to the grand total. Instead, this need is due to the “song-first, words-later” practice in Cantopop songwriting. Since the contrapuntal possibilities are different with the different types of melodic motion, one must consider the text-setting constraint for level and moving song melodies separately. As a result, types I and II of oblique motion should be treated as heterogeneous categories, and the rarity of oblique I motion can then be reconciled with the model of text-setting constraints. 5.2. Pitch range and directionality of oblique II motion In the previous sections, I have focused mainly on the interaction between Cantonese tones and the directionality of song melodies. Nonetheless, the directionality of Cantopop melodies is influenced by many other factors. For example, previous research on cross-cultural corpora of music has shown that when a note in a song melody is near the limit of the melody’s pitch range, the subsequent melodic movement tends to move back towards the average pitch in the range (von Hippel 2000; von Hippel and Huron 2000). That is, when the song melody has reached a pitch near the lowest pitch in the song’s range, the next melodic motion would more likely be upward than downward, and vice versa. Researchers have attributed this propensity to the observation that the distribution of melodic pitches tends to center around the central point of the range and taper off near the extremities (von Hippel 2000; Temperley 2008). The preference of mid-range pitches and the avoidance of pitch extremities may be due to technical limitations in performance: when playing an instrument or singing, midrange pitches are easier 70 to reach than those near the limit of the range (von Hippel 2000, 316). Since pitches in a song melody tend to approach the average value in the range, Huron named this phenomenon after the statistical principle of “regression toward the mean” and called it “melodic regression” (2006, 80). In this section, I focus on the issue regarding the directionality of oblique II motion in Cantopop, particularly for T1 [55]–T1 [55] and T4 [11]–T4[11] bigrams. With oblique II motion, the speech melody stays level while the song melody moves upward or downward. Previous scholars have observed that the direction of song melodies in Cantopop seems to correlate with the tones used in an oblique II bigram (Ho 2010; Ladd, forthcoming). Oblique II bigrams with consecutive high-register tones (T1 [55]–T1 [55]) usually have a downward song melody, where those with consecutive extra-low-register tones (T4 [11]–T4 [11]) tend to have an upward song melody. However, these researchers were not sure if this tendency reflects (1) a propensity for song melodies of a certain direction to be set to pairs of consecutive tones or (2) the tendency of melodic regression. In these previous studies, no information relating to pitch range was reported, and some of these samples were so small that there were “too few cases to be confident” about substantiating either claim (Ladd, forthcoming, 10n). With the current Cantopop corpus, I will investigate the effect of pitch range and melodic regression on the directionality of song melodies by comparing the occurrences of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams.36 5.2.1. Evidence on the opposite directionality and its explanations Many Cantopop scholars have noticed the tendency for T1 [55]–T1 [55] bigrams to have a downward song melody (Ho 2010, 65–66; Chow 2012, 64–66; Lo 2013, 31–32; C. W. Wong 2020, 129–32; Ladd, forthcoming). On the other hand, based on her observation on a few 36 Although T2 [25] is also a high-register tone according to the four-register classification of Cantonese and the endpoint principle, T2 [25]–T2 [25] bigrams are excluded from analysis in this chapter. This is because, as discussed in Chapter 4, there is a difference between the text-setting treatment for level T1 [55] and contour T2 [25]. In order to identify the interaction of tone register and pitch range, I will focus on the comparison between T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. 71 Cantopop passages, Ho (2010, 60–63) also speculated that oblique II bigrams with consecutive T4 [11] (i.e., T4 [11]–T4 [11]) usually have upward song melodies. In other words, oblique II motion for T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams tend to have song melodies in opposite directions. As Ladd tried to confirm Ho’s speculation about the upward propensity of oblique II T4 [11]–T4 [11] bigrams, he found some corroborative evidence from Kirby’s (forthcoming) data but admitted that there were “too few cases to be confident” (Ladd, forthcoming, 10n). In other words, no research to date has offered substantial evidence about the tendency for oblique II T4 [11]–T4 [11] bigrams to have an upward song melody. With the current Cantopop corpus, I verify the observations regarding the opposite directionality of oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. Figure 29 shows the distribution of bigram types given a song melody in a certain direction. T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams are shown as distinct categories since they are the focus of the current section, whereas the remaining 34 bigram types (the square of the six tones minus the two specified bigram types) are grouped together as the category of “others.” Figure 29. Distribution of bigram types given a song melody in a certain direction 72 As shown in Figure 29, it is more probable to find a T1 [55]–T1 [55] or T4 [11]–T4 [11] bigram when the song melody is level. 19.27% of all bigrams with a level song melody (n = 6,195) are set to T1 [55]–T1 [55], and 11.07% to T4 [11]–T4 [11]. These instances constitute similar motion between the song melody and the speech melody. Nonetheless, data regarding downward and upward moving song melodies support the claim about opposite directionality of oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. Of the bigrams with a downward song melody (n = 12,525), 11.54% are set to T1 [55]–T1 [55], whereas only 0.40% are set to T4 [11]–T4 [11]. Conversely, for bigrams with an upward song melody (n = 12,762), 4.07% are set to T4 [11]–T4 [11], whereas only 0.65% to T1 [55]–T1 [55]. Results of a chi-square test show that these differences are statistically significant (p < 0.001), confirming that oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams tend to have song melodies of opposite directions. Oblique II T1 [55]–T1 [55] bigrams are more likely found with a downward song melody, and oblique II T4 [11]–T4 [11] with an upward song melody. This observation is consistent with previous scholars’ observations and warrants further investigation into the factors behind this phenomenon. Some scholars speculated that the tendency for oblique II T1 [55]–T1 [55] to have a downward song melody is due to its resemblance to speech declination (Ho 2010, 66; Ladd, forthcoming, 10). In tone languages, speech declination causes the F0 value of the same tone to decrease as the tone is repeated successively in a sentence. For example, when a Cantonese sentence that consists exclusively of T1 [55] syllables is spoken, the pitch of the final syllable can be lower than that of the first by an interval ranging from a major second to a minor third (Ge and Li 2018, 430). This pitch difference can sufficiently differentiate between tones of different registers (e.g., T1 [55] and T3 [33]) (P. Wong and Chan 2018). When listening to sentences like these, Cantonese speakers are able to implicitly anticipate the effect of speech declination, such that they would expect an overall downward trend in pitch regardless of the tones (Yuen 2007, 75). As a result, despite the downward shift in pitch heights over the course of a sentence, they can correctly discern the words and understand the sentence. 73 In Cantopop, when lyricists set two or more consecutive T1 [55] syllables over a downward song melody, the resulting oblique II motion resembles speech declination, since the tones are remaining the same yet the actual pitch is falling. Therefore, setting a downward song melody to T1 [55]–T1 [55] bigrams is consistent with the listeners’ expectation of speech declination. Accordingly, speech declination might explain why oblique II T1 [55]–T1 [55] bigrams often have a downward moving song melody. While speech declination can plausibly explain why oblique II T1 [55]–T1 [55] bigrams often having downward song melodies, it cannot explain the upward tendency for T4 [11]–T4 [11] bigrams. Ho (2010, 63) speculated that this opposite directionality for oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams might be explained by melodic regression (although she did not explicitly identify this concept). Nonetheless, she provided no evidence to support this explanation. Therefore, currently there is no substantiated explanation as to why these bigram types display different directionality. In this study, I will investigate how the directionality of these oblique II bigrams might be explained by melodic regression. 5.2.2. Evidence related to pitch range in Cantopop text-setting As discussed in Section 5.2.1, previous research has focused on the relationship between the direction of song melody and the occurrence of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. This relationship is labelled by arrow ③ in Figure 30.37 No previous scholars on Cantopop have looked into how pitch range plays a role in tone-melody correspondence. 37 Note that the direction of arrows in Figure 30 symbolizes causal relationship. In this study, it is practical to establish a causal (instead of purely correlational) relationship between the song melody direction and the tones used in a bigram because the music is written before the text in Cantopop (see Section 5.1). 74 Figure 30. Three-way association relating to the opposite directionality for T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams To refine this model, I propose to consider an additional factor—a note’s position in the song’s pitch range (hereafter the “range factor”)—that explains this relationship. I hypothesize that the range factor affects both variables in relationship ③: First, the tendency of melodic regression means that the range factor affects whether the song melody would proceed upward or downward (shown by arrow ① in Figure 30). Second, I propose that T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams tend to occur in different positions in a song’s range (arrow ② in Figure 30). As the result of relationships ① and ②, if oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams are correlated with a certain direction in the song melody (hereafter the “direction factor”), it is because both of them are affected by the range factor. By studying this confounding effect, I argue that the opposite directionality of oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams is attributable to the range factor, which has been overlooked by previous scholars. The occurrence of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams is not only influenced by the direction of the given song melody, but also by the range factor. To test whether melodic regression is a valid generalization for Cantopop, I examine whether the direction of song melody in each bigram is correlated with the range factor. To quantify the range factor, for each bigram I calculate the semitone distance between the first pitch in the bigram and the pitch extremes (i.e., the highest and lowest pitches) in the song’s 75 range. To illustrate this calculation, Figure 31 presents an excerpt from the song “明年今日 (ming4 nin4 gam1 jat6)” (C0205). The range of this song spans 19 semitones, from B♭2 to F4. For example, the first bigram in this excerpt begins on E♭3, which is 14 semitones below the highest pitch in the song’s range and 5 semitones above the lowest, and the song melody proceeds upward from this pitch (approaching the pitch C4). Figure 31. An excerpt from the first prechorus of “明年今日 (ming4 nin4 gam1 jat6)” (C0205) Since melodic regression describes the behaviour of song melodies as they approach the limits of the pitch range, I will only consider distances that are no more than 10 semitones away from the pitch extremes of the song. For example, for the first bigram in Figure 31 (i.e., 人 jan4–總 zung2 [E♭3–C4]), I will only consider its relation to the lowest pitch in the song, but not the highest pitch. This is because the first pitch in the bigram (E♭3) is five semitones above the lowest pitch, but 14 (i.e., more than 10) semitones below the highest pitch. The choice of 10 is based on the distribution of range for the 105 songs in the corpus, which is shown below as Figure 32. The median pitch range is 20 semitones, meaning that for the average song, the central pitch is 10 semitones away from the highest and lowest pitch of the song. In other words, if a pitch is more than 10 semitones away from a pitch extreme, it will likely be closer to the other end of the range than the one in the current calculation. For such cases, it is more 76 meaningful to discuss its interaction with the other extreme in the song’s pitch range. In the following discussion, I will use the terms “lower range condition” and “higher range condition” to refer to the data for bigrams starting no more than 10 semitones from the lowest pitch and the highest pitch respectively. Figure 32. Distribution of pitch range in the corpus Figure 33 shows the distributions of song melody directions based on the distance between the first pitch in each bigram and the pitch extremes in the song, offering evidence of melodic regression in the Cantopop corpus. These distributions demonstrate a clear pattern of the range factor affecting the direction of song melodies in Cantopop (arrow ① in Figure 30). As shown in Figure 33a, the farther a note is from the lowest pitch in a song, the higher the proportion of downward song melodies and the lower the proportion of upward song melodies. Similarly, as shown in Figure 33b, in the higher range condition, there is also a clear correlation between the range factor and the direction of song melodies. As the distance from the highest pitch increases, the proportion of downward song melodies decreases, and that for upward song melodies increases. 77 Figure 33. Distribution of song melody based on distance from pitch extremes In other words, when a note is closer to the lower pitch extreme in song, the subsequent melodic motion tends to be upward, and vice versa. Two separate multinomial logistic regression tests—one for the lower range condition and one for the higher range condition—were conducted to examine whether this pattern of melodic regression in the Cantopop corpus is statistically significant.38 The predictor variable is the distance from the pitch extreme in the given range condition, and the outcome variable is the probabilities for downward and upward song melodies.39 The resulting regression coefficients—transformed in Table 15 into percentage change in odds40—are statistically significant (p < 0.001) and confirm the observations described above. For example, as shown in the first row of Table 15, a semitone increase in the distance from the lowest pitch increases the odds of having a downward song melody (against having a 38 Multinomial logistic regression is a type of regression model used for predicting the probabilities of a categorical outcome, which is the type of song melodies in this case. For a more detailed description of this type of regression analysis, see Long (1997, 148–86), Menard (2002), and Pampel (2021). 39 The probability of having a level song melody is used as a reference group against which the odds for downward and upward melodies are compared. 40 Given a logistic coefficient B, the percentage change in odds is given by the term eB – 1. The concept of odds is related to, but also distinct from the concept of probability. One must not confuse the ratio between odds with other measures of association, such as relative risk (the ratio of probabilities). See Menard (2002, 57) and Spiegelhalter (2019, 34–36) for a description of this distinction. 78 level song melody) by 18.89% and decreases that of having an upward song melody by 5%. As expected, results in the second row of Table 15 validate the opposite trend for distances from the highest pitch. Table 15. Odds ratios for direction of song melodies as predicted by distance from pitch extremes Predictor variable Change in odds for outcome (all p < 0.001) Downward melody Upward melody Distance from the lowest pitch (Lower range condition) +18.89% –4.88% Distance from the highest pitch (Higher range condition) –2.57% +24.48% Having confirmed the occurrence of melodic regression in Cantopop, I proceed to consider whether the range factor also affects the frequency of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams (arrow ② in Figure 30). In my Cantopop corpus, T1 [55]–T1 [55] bigrams are more common in the upper range of a song and T4 [11]–T4 [11] bigrams in the lower range. Figure 34 plots the distribution of bigram types with respect to the distance from pitch extremes. As shown in Figure 34a, among the 595 bigrams that start on the lowest pitch of a song, only 1 of them is set to consecutive T1 [55] syllables. The probability of observing a T1 [55]–T1 [55] bigram increases with the distance from the lowest pitch. By contrast, there is a higher probability (15.97%, 95 out of 595) of finding a T4 [11]–T4 [11] bigram at the lowest pitch in a song’s range, and this probability decreases as the distance from the lowest pitch increases. As shown in Figure 34b, the reverse pattern can be seen in the higher range condition. T1 [55]–T1 [55] bigram accounts for more than 20% (141 out of 551) of bigrams at the highest pitch of the range, whereas T4 [11]–T4 [11] bigrams can only be found when the bigram starts on at least 4 semitones away from the highest pitch in the song. As the distance from the highest pitch of the range increases, the frequency of having a T1 [55]–T1 [55] bigram decreases and that of a T4 [11]–T4 [11] bigram increases. 79 Figure 34. Distribution of bigram types based on distance from the pitch extremes Results from multinomial regression tests, listed in Table 16, agree with the effect of the range factor on the frequency of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. All these odds ratios—the ratio between the odds of observing the predicted bigram type and against that of having a bigram in the “others” category—are in line with the pattern visualized in Figure 34 and are statistically significant (p < 0.001). In other words, the range factor has an effect on the frequency of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams: T1 [55]–T1 [55] bigrams become more common as the starting pitch of a bigram approaches the higher range, and T4 [11]–T4 [11] bigrams become more common as the starting pitch of a bigram approaches the lower range. Table 16. Odds ratios for T1–T1 and T4–T4 bigrams as predicted by distance from pitch extremes Predictor variable Change in odds for outcome T1 [55]–T1 [55] T4 [11]–T4 [11] Distance from the lowest pitch (Lower range condition) +29.56% –17.30% Distance from the highest pitch (Higher range condition) –16.81% +56.05% 80 5.2.3. Considering the range factor and the direction factor In Sections 5.2.1 and 5.2.2, I demonstrated that all three effects in Figure 30 are present in the current Cantopop corpus: The range factor affects both the direction of song melody and the frequency of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams (arrows ① and ② in Figure 30, respectively). At the same time, the direction factor—which is affected by the range factor through arrow ①—also has an effect on the oblique II motion for T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams (arrow ③ in Figure 30): oblique II T1 [55]–T1 [55] bigrams are more likely to be found with a downward song melody, and oblique II T4 [11]–T4 [11] with an upward song melody. Therefore, to test my hypothesis that the range factor plays an independent role in affecting the directionality of oblique II motion for T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams, I reexamine the distribution of bigram types based on the distance between the starting pitch of bigrams and the pitch extremes—that is, in the manner of Figure 34—while holding the direction of the song melody constant. I stratify the data into three groups, according to whether the song melody of the bigram is downward, level, or upward, and observe whether the effect of the range factor on the distribution of bigram types is still present. Since the current focus is on oblique II motion, only observations related to downward and upward song melodies will be discussed. Following the format of Figure 34, Figures 35 and 36 plot the distribution of bigram types with downward and upward melodies respectively. These figures clearly demonstrate a pattern that is similar to the one shown in Figure 34. That is, as the starting pitch of a bigram approaches the highest pitch in a song, T1 [55]–T1 [55] bigrams become more common. At the same time, T4 [11]–T4 [11] bigrams are more common towards the lowest pitch. 81 Figure 35. Distribution of bigram types with downward song melodies based on distance from the pitch extremes Multinomial logistic regression tests were run to test the significance of these four distributions—that is, both the lower range and the higher range conditions for the data subset of downward and upward song melodies. Results for all four distributions are found to be statistically significant. The regression coefficients—translated into the percentage change in odds—and the corresponding p-values are listed in Table 17. The results show that, regardless of the direction of the song melody, the range factor influences the frequency of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. As shown in Figure 35, given a downward melody, T1 [55]–T1 [55] bigrams are still more common in the higher range of a song. Therefore, the tendency to find a T1 [55]–T1 [55] bigram with a downward song melody cannot be explained by the direction factor alone. The range factor also plays a part. Since T1 [55]–T1 [55] bigrams tend to occur in the higher range regardless of the direction of the song melody, and bigrams in the higher range tend to have a downward song melody, oblique 82 II motion for T1 [55]–T1 [55] bigrams is more likely to be downward than upward. Similarly, T4 [11]–T4 [11] bigrams become more common in the lower range, regardless of the direction of the song melody. And because song melodies in the lower range tend to go up melodically, oblique II motion for T4 [11]–T4 [11] bigrams is mostly upward. Figure 36. Distribution of bigram types with upward song melodies based on distance from the pitch extremes The above observations serve to describe the intricate interaction between the range factor and direction factor. In this section, I show that both the range factor and the direction factor contribute to the opposite directionality of oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. The effect of the range factor can be seen in the fact that the occurrence of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams tend to concentrate in the higher and lower range respectively, regardless of the direction of the song melody. At the same time, the direction factor also affects how the bigram types are distributed: by comparing the yellow and green areas in Figures 35 and 36, one can see that in both range conditions, T1 [55]–T1 [55] bigrams are 83 more common with a song melody that is downward whereas T4 [11]–T4 [11] with one that is upward. Table 17. Odds ratios for T1–T1 and T4–T4 bigrams as predicted by distance from pitch extremes, after controlling for the direction of the song melody Direction of the song melody Predictor variable Change in odds for outcome T1 [55]–T1 [55] T4 [11]–T4 [11] Downward Distance from the lowest pitch (Lower range condition) +23.51%* –17.48%^ Distance from the highest pitch (Higher range condition) –12.30%* +44.55%* Upward Distance from the lowest pitch (Lower range condition) +54.41%* –12.56%* Distance from the highest pitch (Higher range condition) –29.77%* +34.66%* *: p < 0.001; ^: p = 0.003 To sum up, I have found strong statistical evidence concerning the influence of the range factor in tone-melody correspondence in Cantopop—particularly the phenomenon of melodic regression whereby the direction of song melody correlates with a note’s position in a song’s range. By considering the presence of the range factor, I propose that the opposite directionality of oblique II T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams is attributable to the tendency of melodic regression. Since pitches in the lower range would generally tend to go up and vice versa, it is natural for T1 [55]–T1 [55] bigrams—which are often found in the higher register—to show oblique II motion with a downward song melody and for T4 [11]–T4 [11] bigrams—often found in the lower register—to show oblique II motion with an upward song melody. By introducing the concept of melodic regression to Cantopop research, my analysis offers a more comprehensive account as to why oblique II motion for T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams have opposite directionality. In future research on tone-melody correspondence in Cantopop, the role of pitch range may play a more decisive role in describing text-setting constraints for the genre. 84 6. Conclusion This study explores two theoretical issues related to tone-melody correspondence in Cantopop: the first concerns the treatment of contour tones vis-à-vis level tones, and another deals with oblique motion between the song melody and the speech melody. First, in Chapter 4, I critically examine the endpoint principle, the commonly accepted assumption that contour tones and their level counterpart are treated as equivalent in Cantopop text-setting, due to their identical tonal targets. Quantitative evidence from my corpus indicates that this principle has failed to capture the subtlety of contour tone text-setting. I argue that contour tones are set more flexibly than their level counterpart because of the additional perceptual cue of an upward glide that reflects the rising contour of contour tones. This cue aids the listener in discerning the lyrics correctly, such that the text-setting constraint may be relaxed for bigrams with contour tones. This explains why oblique motion is more common for contour tone bigrams than bigrams with only level tones, as shown in my corpus data. This new finding supplements the endpoint principle by justifying instances where the setting of contour tour bigrams seems to challenge the principle. Second, in Chapter 5, I examine questions regarding oblique motion in Cantopop text-setting. First of such questions concerns the seemingly paradoxical rarity of oblique I motion in Cantopop, given that the text-setting constraint for tone language music prefers oblique motion to contrary motion. Based on the typical text-setting process of Cantopop, I justify the infrequent occurrence of oblique I motion by proposing a revised way of examining the data: by considering level and moving song melodies separately, I argue that the frequency of oblique I motion should not be directly compared with that of oblique II and contrary motion. In other words, the text-setting constraint should be described differently for level versus moving song melodies. Empirical data from the current corpus indicate that this new perspective can reconcile the rarity of oblique I motion with the text-setting constraint. Another question concerning oblique motion is related to the observation that oblique II T1 [55]–T1 [55] and 85 T4 [11]–T4 [11] bigrams tend to have song melodies of opposite directions. I propose that the directionality of these bigram types is also affected by the range factor—that is, a note’s position in a song’s pitch range. I consider the general phenomenon of melodic regression and the range factor when modelling the occurrence of the bigram types in question. My analysis shows that both the range factor and the direction factor are significant predictors for the occurrence of T1 [55]–T1 [55] and T4 [11]–T4 [11] bigrams. In other words, the opposite directionality of oblique II motion for these two bigram types is attributable to the effect of melodic regression, which is not examined in previous research on tone-melody correspondence in Cantopop. In terms of methodology, this study contributes to the research on Cantopop by constructing the first representative corpus of the genre. In previous research on tone-melody correspondence in Cantopop, musical examples were chosen without sufficient justification and without considering their representativeness. Some studies also have the problem of using only isolated passages from selected songs to justify claims that are presented as general observation for the genre. Therefore, by creating a much larger corpus with clearly outlined selection criteria, this study improves the reliability of the findings and lays the groundwork for future research on Cantopop. Although in this study I have only looked at a few research problems, the corpus has the potential for answering a much larger range of questions related to the genre. For example, if one wishes to extend the current enquiry into tone-melody correspondence in Cantopop, my corpus data can also offer information about how song melodies in certain bigram types tend to be distributed around a few interval sizes. (For those who are interested, Appendix B offers a table listing the counts of each interval sizes for each bigram type.) Another example of a potential use of this corpus is the study of how different Cantopop lyricists set their lyrics differently, as the corpus includes a substantial amount of works by the two prominent lyricists Lin Xi and Wyman Wong (see Section 3.3 and Figure 4). Beyond the study of tone-melody correspondence, my Cantopop corpus can also be a starting point for investigations related to other aspects of Cantopop, such as rhythmic features, formal design, and harmonic 86 progressions. The range of questions that can be answered with the support of the corpus is enormous, and the vast amount of data will constitute substantial quantitative evidence. The empirical approach of this study can also be applied to the study of other musical genres in the Cantonese language, such as Cantonese opera and folk songs. Previous research has suggested that, even within the same language, the degree of tone-melody correspondence varies across genres (Schellenberg 2012). While this study has offered extensive data about tone-melody correspondence in Cantopop, future research should extend this methodology to consider other genres of Cantonese music. By comparing the data from Cantopop and other Cantonese musical genres, the interaction between Cantonese tones ang song melody can be more fully understood. An important limitation of this study is that I have only considered tone-melody correspondence in Cantopop only with respect to the types of bigrams—that is, the succession of two syllables in the speech melody and two pitches in the song melody. However, it might be more sensible to say that tone-melody correspondence in Cantopop operates across a span longer than a bigram. In future research, and by extracting data from the corpus differently, it will be interesting and enlightening to examine how the song melody and the speech melody correlate with each other across a longer span. Another limitation of this study is that I have implicitly assumed that the frequency of bigram types is positively correlated with their perceived intelligibility, but that might not always be the case. Bigram types that are rarely found in the corpus could still be perfectly intelligible to listeners, whereas common ones may cause ambiguity in meaning in some contexts. To examine the validity of this assumption, a closer examination of the data is required, and perception tests would also offer valuable evidence. By reconsidering claims from previous research on tone-melody correspondence in Cantopop and using an improved methodology, this study has offered new insights as to how these previous observations should be understood and how previously unexamined factors affect the treatment of linguistic tones in Cantopop text-setting. Nonetheless, as Kirby has put it, 87 the quantitative research on tone-melody correspondence in Cantopop is still in its early stages and “we are still at what we might call the constraint-discovery stage in the study of tone-melody correspondences” (forthcoming, 15). But this study and the corresponding corpus will pave the way for more substantial attempts to understand this topic. 88 Bibliography Agawu, V. Kofi. 2016. The African Imagination in Music. New York: Oxford University Press. Alderete, John, Queenie Chan, and Shin-Ichi Tanaka. 2022. “The Morphology of Cantonese ‘Changed Tone’: Extensions and Limitations.” 言語研究 Gengo Kenkyu 161: 139–69. Attas, Robin. 2011. “Sarah Setting the Terms: Defining Phrase in Popular Music.” Music Theory Online 17 (3). https://mtosmt.org/issues/mto.11.17.3/mto.11.17.3.attas.html. Baart, Joan. 2004. “Tone and Song in Kalam Kohistani (Pakistani).” In On Speech and Language: Studies for Sieb G. Nooteboom, edited by Hugo Quené and Vincent van Heuven, 5–15. Utrecht: Netherlands Graduate School of Linguistics. BaileyShea, Matthew L. 2021. Lines and Lyrics: An Introduction to Poetry and Song. New Haven, CT: Yale University Press. Bauer, Robert S., and Paul K. Benedict. 1997. Modern Cantonese Phonology. Trends in Linguistics: Studies and Monographs 102. Berlin and New York: Mouton de Gruyter. Bauer, Robert S., Kwan-Hin Cheung, and Pak-Man Cheung. 2003. “Variation and Merger of the Rising Tones in Hong Kong Cantonese.” Language Variation and Change 15 (2): 211–25. https://doi.org/10.1017/S0954394503152039. Bennett, Ryan, and Emily Elfner. 2019. “The Syntax–Prosody Interface.” Annual Review of Linguistics 5 (1): 151–71. https://doi.org/10.1146/annurev-linguistics-011718-012503. Biamonte, Nicole. 2010. “Triadic Modal and Pentatonic Patterns in Rock Music.” Music Theory Spectrum 32 (2): 95–110. Callahan, Michael R. 2013. “Sentential Lyric-Types in the Great American Songbook.” Music Theory Online 19 (3). https://www.mtosmt.org/issues/mto.13.19.3/mto.13.19.3.callahan.html. Ceccagno, Antonella. 2016. “Chinese Neologisms: Word-Formation Strategies in Chinese.” In The Routledge Encyclopedia of the Chinese Language, edited by Sin-wai Chan, 227–41. London and New York: Routledge. Chan, Brian Hok-Shing. 2009. “English in Hong Kong Cantopop: Language Choice, Code-Switching and Genre.” World Englishes 28 (1): 107–29. https://doi.org/10.1111/j.1467-971X.2008.01572.x. Chan, Kai Young. Forthcoming. “From Constraints to Creativity: Musical Inventions through Cantonese Contours in Hong Kong Contemporary Music.” Principles of Music Composing 20. Chan, Ka-ming 陳嘉銘, Billy Tsz-yu Ng 吳子瑜, and Sea 海邊欄. 2022. 給下一輪廣東歌盛世備忘錄—香港樂壇變奏 Memos for Canto-Pop in the next Millennium. Hong Kong: Breakthrough. 89 Chan, Marjorie K. M. 1987a. “Tone and Melody in Cantonese.” Proceedings of the Thirteenth Annual Meeting of the Berkeley Linguistics Society, 26–37. ———. 1987b. “Tone and Melody Interaction in Cantonese and Mandarin Songs.” UCLA Working Papers in Phonetics 68 (July). Chan, Marjorie K. M., and Jocelyn Chey. 2013. “‘Love You to the Bone’ and Other Songs: Humour and Rusheng Rhymes in Early Cantopop.” In Humour in Chinese Life and Culture: Resistance and Control in Modern Times, edited by Jessica Milner Davis and Jocelyn Chey, 103–30. Hong Kong: Hong Kong University Press. https://doi.org/10.5790/hongkong/9789888139231.003.0005. Chao, Yuen Ren. 1930. “A System of ‘Tone-Letters.’” Le Maître Phonétique 45 (30): 24–27. ———. 1947. Cantonese Primer. Cambridge, MA: Harvard University Press. Cheng, Siu-Pong, and Sze-Wing Tang. 2016. “Cantonese.” In Routledge Encyclopedia of the Chinese Language, edited by Sin-wai Chan, 18–34. Oxon and New York: Routledge. Chen-Hafteck, Lily. 1999. “Singing Cantonese Children’s Songs: Significance of the Pitch Relationship between Text and Melody.” Music Education Research 1 (1): 93–108. https://doi.org/10.1080/1461380990010108. Cheung, Kwan-Hin 張群顯. 2016. “從中古四聲到現代粵語六調 From Ping-Shang-Qu-Ru of Middle Chinese to the Six Tones of Present-Day Cantonese.” In 漢語研究的新貌：方言、語法與文獻 New Horizons in the Study of Chinese: Dialectology, Grammar, and Philology, 361–83. Hong Kong: T.T. Ng Chinese Language Research Centre. Chik, Alice. 2010. “Creative Multilingualism in Hong Kong Popular Music.” World Englishes 29 (4): 508–22. https://doi.org/10.1111/j.1467-971X.2010.01678.x. Choi, William. 2020. “The Selectivity of Musical Advantage: Perceptual Advantage for Some but Not All Cantonese Tones.” Music Perception 37 (5): 423–34. https://doi.org/10.1525/mp.2020.37.5.423. Chow, Man Ying. 2012. “Singing the Right Tones of the Words: The Principles and Poetics of Tone-Melody Mapping in Cantopop.” MPhil diss., The University of Hong Kong. Chu, Yiu-Wai. 2017. Hong Kong Cantopop: A Concise History. Hong Kong: Hong Kong University Press. Chu, Yiu-Wai 朱耀偉, and Wai-Sze Leung 梁偉詩. 2015. 後九七香港粵語流行歌詞研究 I [Post-97 Hong Kong Cantopop Lyrics Study I]. 2nd ed. Hong Kong: Enlighten & Fish. Chung, Winnie. 2001. “No Unification yet for Hong Kong Awards.” Billboard, December 1, 2001. Cook, Nicholas. 2004. “Computational and Comparative Musicology.” In Empirical Musicology: Aims, Methods, Prospects, edited by Eric Clarke and Nicholas Cook, 103–126. New York: Oxford University Press. 90 de Clercq, Trevor. 2021a. “How Should Corpus Studies of Harmony in Popular Music Handle the Minor Tonic?” In Proceedings of Future Directions Music Cognition Conference, 43–48. https://kb.osu.edu/handle/1811/93177 ———. 2021b. “The Logic of Six-Based Minor for Harmonic Analyses of Popular Music.” Music Theory Online 27 (4). https://mtosmt.org/issues/mto.21.27.4/mto.21.27.4.de_clercq.html. de Clercq, Trevor, and David Temperley. 2011. “A Corpus Analysis of Rock Harmony.” Popular Music 30 (1): 47–70. https://doi.org/10.1017/S026114301000067X. Deutsch, Diana. 2019. Musical Illusions and Phantom Words: How Music and Speech Unlock Mysteries of the Brain. New York: Oxford University Press. Devaney, Johanna, and Hubert Léveillé Gauvin. 2019. “Encoding Music Performance Data in Humdrum and MEI.” International Journal on Digital Libraries 20 (1): 81–91. https://doi.org/10.1007/s00799-017-0229-3. Doll, Christopher. 2017. Hearing Harmony: Toward a Tonal Theory for the Rock Era. Ann Arbor: University of Michigan Press. ———. 2018. “Some Practical Issues in the Aesthetic Analysis of Popular Music.” In The Routledge Companion to Popular Music Analysis: Expanding Approaches, edited by Ciro Scotto, Kenneth Smith, and John Brackett, 3–14. New York: Routledge. Eberhard, David M., Gary F. Simons, and Charles D. Fennig, eds. 2022. Ethnologue: Languages of the World. 25th ed. Dallas, TX: SIL International. https://www.ethnologue.com/. Flynn, Choi-Yeung-Chang. 2001. “Intonation in Cantonese.” PhD diss., School of Oriental and African Studies, University of London. Fung, Anthony, and Alice Chik. 2020. “Introduction: Mainstreaming Hong Kong Popular Music.” In Made in Hong Kong: Studies in Popular Music. Routledge. Fung, Roxana S. Y., and Chris K. C. Lee. 2019. “Tone Mergers in Hong Kong Cantonese: An Asymmetry of Production and Perception.” The Journal of the Acoustical Society of America 146 (5): EL424–30. https://doi.org/10.1121/1.5133661. Ge, Chunyu, and Aijun Li. 2018. “Declination and Boundary Effect in Cantonese Declarative Sentence.” In 2018 11th International Symposium on Chinese Spoken Language Processing (ISCSLP), 429–33. https://doi.org/10.1109/ISCSLP.2018.8706677. Gompel, Roger P. G. van, and Martin J. Pickering. 2012. “Syntactic Parsing.” In The Oxford Handbook of Psycholinguistics, edited by M. Gareth Gaskell, 289–308. Oxford University Press. https://doi.org/10.1093/oxfordhb/9780198568971.013.0017. Gu, Wentao, Keikichi Hirose, and Hiroya Fujisaki. 2007. “Analysis of Tones in Cantonese Speech Based on the Command-Response Model.” Phonetica 64 (1): 29–62. https://doi.org/10.1159/000100060. 91 Herzog, George. 1934. “Speech-Melody and Primitive Music.” The Musical Quarterly 20 (4): 452–66. Ho, Vincie W. S. 2006. “The Tone-Melody Interface of Popular Songs Written in Tone Languages.” Proceedings of the 9th International Conference on Music Perception and Cognition, Bologna, 1414–22. ———. 2010. “A Phonological Study of the Tone-Melody Correspondence in Cantonese Pop Music.” PhD diss., The University of Hong Kong. Huron, David. 2002. “Music Information Processing Using the Humdrum Toolkit: Concepts, Examples, and Lessons.” Computer Music Journal 26 (2): 11–26. ———. 2006. Sweet Anticipation: Music and the Psychology of Expectation. Cambridge, MA and London: MIT Press. ———. 2013. “On the Virtuous and the Vexatious in an Age of Big Data.” Music Perception: An Interdisciplinary Journal 31 (1): 4–9. https://doi.org/10.1525/mp.2013.31.1.4. Hyman, Larry M. 2011. “Tone: Is It Different?” In The Handbook of Phonological Theory, edited by John Goldsmith, Jason Riggle, and Alan C. L. Yu, 2nd ed., 197–239. Chichester: Wiley-Blackwell. Jäncke, Lutz. 2012. “The Relationship between Music and Language.” Frontiers in Psychology 3: Article 123. Karlsson, Anastasia. 2018. “Coordination between Lexical Tones and Melody in Traditional Kammu Singing.” Journal of the Phonetic Society of Japan 22 (3): 30–41. https://doi.org/10.24467/onseikenkyu.22.3_30. Ketkaew, Chawadon, and Pittayawat Pittayaporn. 2014. “Mapping between Lexical Tones and Musical Notes in Thai Pop Songs.” In Proceedings of the 28th Pacific Asia Conference on Language, Information and Computing, 160–69. https://aclanthology.org/Y14-1021. Khouw, Edward, and Valter Ciocca. 2007. “Perceptual Correlates of Cantonese Tones.” Journal of Phonetics 35 (1): 104–17. https://doi.org/10.1016/j.wocn.2005.10.003. Kirby, James. 2021. “Towards a Comparative History of Tonal Text-Setting Practices in Southeast Asia.” In Transcultural Music History: Global Participation and Regional Diversity in the Modern Age, edited by Reinhard Strohm, 291–312. Berlin: Berliner Wissenschafts-Verlag. ———. Forthcoming. “Comparative Tonal Text-Setting in Mandarin and Cantonese Popular Song.” Proceedings of the Chicago Linguistic Society. Kirby, James, and D. Robert Ladd. 2016. “Tone-Melody Correspondence in Vietnamese Popular Song.” In 5th International Symposium on Tonal Aspects of Languages (TAL 2016), 48–51. https://doi.org/10.21437/TAL.2016-10. Komaniecki, Robert. 2020. “Vocal Pitch in Rap Flow.” Intégral 34: 25–45. 92 Kurpaska, Maria. 2019. “Varieties of Chinese: Dialects or Sinitic Languages.” In The Routledge Handbook of Chinese Applied Linguistics, edited by Chu-Ren Huang, Zhuo Jing-Schmidt, and Barbara Meisterernst, 182–95. London: Routledge. Ladd, D. Robert. Forthcoming. “Two Problems in Theories of Tone-Melody Matching.” Studies in Prosodic Grammar. Ladd, D. Robert, and James Kirby. 2020. “Tone-Melody Matching in Tone-Language Singing.” In The Oxford Handbook of Language Prosody, edited by Carlos Gussenhoven and Aoju Chen, 676–87. Oxford: Oxford University Press. Lau, Luciana Siu Ping, and Chris J. James. 2004. “A Tonal Language Test of Speech Perception: Cantonese Spondee Lists.” Asia Pacific Journal of Speech, Language and Hearing 9 (3): 200–219. https://doi.org/10.1179/136132804805575877. Lee, Tan, Wai Lau, Y W Wong, and P C Ching. 2002. “Using Tone Information in Cantonese Continuous Speech Recognition.” ACM Transactions on Asian Language Information Processing 1 (1): 83–102. Lerdahl, Fred, and Ray S. Jackendoff. 1983. A Generative Theory of Tonal Music. MIT Press. Leung, Man-Tak, Sam-Po Law, and Suk-Yee Fung. 2004. “Type and Token Frequencies of Phonological Units in Hong Kong Cantonese.” Behavior Research Methods, Instruments, & Computers 36 (3): 500–505. https://doi.org/10.3758/BF03195596. Li, Edwin K.C. 2021. “Cantopop and Speech-Melody Complex.” Music Theory Online 27 (1). https://mtosmt.org/issues/mto.21.27.1/mto.21.27.1.li.html. Lin, Xi 林夕. 2022. 別人的歌+我的詞 [Their Songs+my Lyrics]. Taipei: Enlighten & Fish. Lo, Tsz Chun. 2013. “Correspondences between Lexical Tone and Music Transitions in Cantonese Pop Songs: A Quantitative and Analytic Approach.” MA dissertation, University of Edinburgh. London, Justin. 2013. “Building a Representative Corpus of Classical Music.” Music Perception 31 (1): 68–90. https://doi.org/10.1525/MP.2013.31.1.68. Long, J. Scott. 1997. Regression Models for Categorical and Limited Dependent Variables. Advanced Quantitative Techniques in the Social Sciences Series 7. Thousand Oaks, CA: Sage Publications. Malawey, Victoria. 2020. A Blaze of Light in Every Word: Analyzing the Popular Singing Voice. New York: Oxford University Press. Marsden, Alan. 2022. “Reliability and Validity of Research with Corpora of Music.” In The Oxford Handbook of Music and Corpus Studies, edited by Daniel Shanahan, John Ashley Burgoyne, and Ian Quinn. New York: Oxford University Press. https://doi.org/10.1093/oxfordhb/9780190945442.013.7. 93 Matthews, P. H. 2014. “Minimal Pair.” In The Concise Oxford Dictionary of Linguistics. Oxford University Press. Matthews, Stephen, and Virginia Yip. 2011. Cantonese: A Comprehensive Grammar. 2nd ed. London and New York: Routledge. McPherson, Laura, and Kevin M. Ryan. 2018. “Tone-Tune Association in Tommo So (Dogon) Folk Songs.” Language 94 (1): 119–56. https://doi.org/10.1353/lan.2018.0003. Menard, Scott. 2002. Applied Logistic Regression Analysis. 2nd ed. Quantitative Applications in the Social Sciences. Thousand Oaks, CA: Sage Publications. Moore, Allan F. 2012. Song Means: Analysing and Interpreting Recorded Popular Song. Farnham, England: Ashgate. Ng, Chi Wui. 2021. “Cantonese-English Code-Switching in Cantopop Television Drama Theme Songs.” World Englishes 40 (3): 354–70. https://doi.org/10.1111/weng.12466. Nobile, Drew. 2020. “Double-Tonic Complexes in Rock Music.” Music Theory Spectrum 42 (2): 207–26. https://doi.org/10.1093/mts/mtaa003. Ohriner, Mitchell. 2019. “Analysing the Pitch Content of the Rapping Voice.” Journal of New Music Research 48 (5): 413–33. https://doi.org/10.1080/09298215.2019.1609525. Pampel, Fred C. 2021. Logistic Regression: A Primer. 2nd ed. Vol. 132. Quantitative Applications in the Social Sciences. Thousand Oaks, CA: Sage Publications. https://doi.org/10.4135/9781071878729. Peng, Gang. 2006. “Temporal and Tonal Aspects of Chinese Syllables: A Corpus-Based Comparative Study of Mandarin and Cantonese.” Journal of Chinese Linguistics 34 (1): 134–54. Pooley, Thomas M. 2020. “Linguistic Tone and Melody in the Singing of Sub-Saharan Africa.” In The Routledge Companion to Interdisciplinary Studies in Singing, Volume I: Development, edited by Frank A. Russo, Beatriz Ilari, and Annabel J. Cohen, 108–20. New York: Routledge. Potter, John. 2006. “Beggar at the Door: The Rise and Fall of Portamento in Singing.” Music & Letters 87 (4): 523–50. Richards, Mark. 2017. “Tonal Ambiguity in Popular Music’s Axis Progressions.” Music Theory Online 23 (3). https://mtosmt.org/issues/mto.17.23.3/mto.17.23.3.richards.html. Rizzo, Mario J., and Douglas Glen Whitman. 2003. “The Camel’s Nose Is in the Tent: Rules, Theories and Slippery Slopes.” UCLA Law Review 51 (2): 539–92. https://doi.org/10.2139/ssrn.352981. Robins, Jeremy M. 2017. “Phrase Structure, Hypermeter, and Closure in Popular Music.” PhD diss., Florida State University. Rothstein, William. 1989. Phrase Rhythm in Tonal Music. New York: Schirmer. 94 Schellenberg, Murray. 2012. “Does Language Determine Music in Tone Languages?” Ethnomusicology 56 (2): 266–78. ———. 2013. “The Realization of Tone in Singing in Cantonese and Mandarin.” PhD diss., The University of British Columbia. Schellenberg, Murray, and Bryan Gick. 2020. “Microtonal Variation in Sung Cantonese.” Phonetica 77 (2): 83–106. https://doi.org/10.1159/000493755. Sleeper, Morgan, and Griselda Reyes Basurto. 2022. “Musicolinguistic Documentation: Tone & Tune in Tlahuapa Tù’un Sàví Songs.” Language Documentation & Convervation 16: 168–208. Sollis, Michael. 2010. “Tune–Tone Relationships in Sung Duna Pikono.” Australian Journal of Linguistics 30 (1): 67–80. https://doi.org/10.1080/07268600903134038. Spicer, Mark. 2017. “Fragile, Emergent, and Absent Tonics in Pop and Rock Songs.” Music Theory Online 23 (2). https://mtosmt.org/issues/mto.17.23.2/mto.17.23.2.spicer.html. Spiegelhalter, David. 2019. The Art of Statistics: Learning from Data. London: Pelican Books. Sprent, Peter. 2010. “Fisher Exact Test.” In International Encyclopedia of Statistical Science, edited by Miodrag Lovric, 524–25. Berlin and Heidelberg: Springer. https://doi.org/10.1007/978-3-642-04898-2_253. Summach, Jay. 2011. “The Structure, Function, and Genesis of the Prechorus.” Music Theory Online 17 (3). https://mtosmt.org/issues/mto.11.17.3/mto.11.17.3.summach.html Tan, Ivan, Ethan Lustig, and David Temperley. 2019. “Anticipatory Syncopation in Rock: A Corpus Study.” Music Perception 36 (4): 353–70. https://doi.org/10.1525/mp.2019.36.4.353. Temperley, David. 2007. “The Melodic-Harmonic ‘Divorce’ in Rock.” Popular Music 26 (2): 323–42. ———. 2008. “A Probabilistic Model of Melody Perception.” Cognitive Science 32 (2): 418–44. https://doi.org/10.1080/03640210701864089. ———. 2017. “Rhythmic Variability in European Vocal Music.” Music Perception: An Interdisciplinary Journal 35 (2): 193–99. ———. 2018. The Musical Language of Rock. New York: Oxford University Press. ———. 2022. “Music and Language.” Annual Review of Linguistics 8 (1): 153–70. https://doi.org/10.1146/annurev-linguistics-031220-121126. Temperley, David, and Trevor de Clercq. 2013. “Statistical Analysis of Harmony and Melody in Rock Music.” Journal of New Music Research 42 (3): 187–204. https://doi.org/10.1080/09298215.2013.788039. Temperley, David, and Leigh VanHandel. 2013. “Introduction to the Special Issues on Corpus Methods.” Music Perception 31 (1): 1–3. https://doi.org/10.1525/mp.2013.31.1.1. 95 Tsui, Wan-Ching 徐允清. 2018. 香港流行曲: 旋律與詩詞的衝擊 Tunes and Verses in Mutual Impact: Hong Kong Popular Songs. Hong Kong: Infolink Publishing. von Hippel, Paul. 2000. “Redefining Pitch Proximity: Tessitura and Mobility as Constraints on Melodic Intervals.” Music Perception 17 (3): 315–27. https://doi.org/10.2307/40285820. von Hippel, Paul, and David Huron. 2000. “Why Do Skips Precede Reversals? The Effect of Tessitura on Melodic Structure.” Music Perception: An Interdisciplinary Journal 18 (1): 59–85. https://doi.org/10.2307/40285901. Wee, Lian-Hee. 2019. Phonological Tone. Cambridge University Press. White, Christopher William, Joe Pater, and Mara Breen. 2022. “A Comparative Analysis of Melodic Rhythm in Two Corpora of American Popular Music.” Journal of Mathematics and Music 16 (2): 160–82. https://doi.org/10.1080/17459737.2022.2075946. Wild, Jonathan. 1996. “A Review of the Humdrum Toolkit: UNIX Tools for Musical Research, Created by David Huron.” Music Theory Online 2 (7). https://www.mtosmt.org/issues/mto.96.2.7/mto.96.2.7.wild.html. Wong, Chi Wah 黃志華. 2020. 文字聲律與粵語歌創作 [Linguistic Tones and Cantonese Songwriting]. Hong Kong: Legend. Wong, Jum Sum. 2003. “The Rise and Decline of Cantopop: A Study of Hong Kong Popular Music (1949–1997).” PhD diss., The University of Hong Kong. Wong, Patrick C.M., and Randy L. Diehl. 2002. “How Can the Lyrics of a Song in a Tone Language Be Understood?” Psychology of Music 30 (2): 202–9. https://doi.org/10.1177/0305735602302006. Wong, Puisan, and Hoi-Yin Chan. 2018. “Acoustic Characteristics of Highly Distinguishable Cantonese Entering and Non- Entering Tones.” The Journal of the Acoustical Society of America 143 (2): 765–79. Xu, Shun-Jie 許舜傑. 2018. “形式的歷史：百年新詩發展綱領 A History of Form: A Sketch of Modern Chinese Poetry Development (1917-2017).” 臺灣詩學學刊 Bulletin of Taiwanese Poetics 31 (May): 133–64. Yang, Helan 楊漢倫, and Siu-Wah Yu 余少華. 2013. 粵語歌曲解讀: 蛻變中的香港聲音 Reading Cantonese Songs: The Voice of Hong Kong through Vicissitudes. Hong Kong: Infolink Publishing. Yin, John Jing-hua. 2016. “Chinese Characters.” In The Routledge Encyclopedia of the Chinese Language, edited by Sin-wai Chan, 51–63. London and New York: Routledge. Yiu, Suki S. Y. 2013. “Cantonese Tones and Musical Intervals.” The International Conference on Phonetics of the Languages in China 2013, 155–58. 96 Yuen, Ivan. 2007. “Declination and Tone Perception in Cantonese.” In Tones and Tunes: Experimental Studies in Word and Sentence Prosody, edited by Carlos Gussenhoven and Tomas Riad, 2:63–77. Berlin: Mouton de Gruyter. Yung, Bell. 1983. “Creative Process in Cantonese Opera I: The Role of Linguistic Tones.” Ethnomusicology 27 (1): 29–47. ———. 1989. Cantonese Opera: Performance as Creative Process. Cambridge: Cambridge University Press. Zee, Eric. 1999. “Chinese (Hong Kong Cantonese).” In Handbook of the International Phonetic Association: A Guide to the Use of the International Phonetic Alphabet, 58–60. Cambridge and New York: Cambridge University Press. Zhang, Ling. 2012. “Intonation Effects on Cantonese Lexical Tones in Speaking and Singing.” PhD diss., The Hong Kong Polytechnic University. Zhang, Xi, and Ian Cross. 2021. “Analysing the Relationship between Tone and Melody in Chaozhou Songs.” Journal of New Music Research. https://doi.org/10.1080/09298215.2021.1974490. 97 Appendices Appendix A: List of the 105 Cantopop songs included in the corpus ID Song Title Year Singer Composer Lyricist C0001 K歌之王 2000 陳奕迅 Eason Chan 陳輝陽 Keith Chan 林夕 Lin Xi C0002 少女的祈禱 2000 楊千嬅 Miriam Yeung 陳輝陽 Keith Chan 林夕 Lin Xi C0003 給⾃⼰的情書 2000 王菲 Faye Wong C.Y. Kong 林夕 Lin Xi C0004 感情線上 2000 鄭秀⽂ Sammi Cheng 黃嘉倩 Cacine Wong 林夕 Lin Xi C0005 活著 Viva 2000 謝霆鋒 Nicholas Tse 謝霆鋒 Nicholas Tse 林夕 Lin Xi C0101 Shall We Talk 2001 陳奕迅 Eason Chan 陳輝陽 Keith Chan 林夕 Lin Xi C0102 最愛演唱會 2001 陳慧琳 Kelly Chen 伍樂城 Ronald Ng 林夕 Lin Xi C0103 爛泥 2001 許志安 Andy Hui 李峻⼀ Joe Lei 李峻⼀ Joe Lei C0104 終⾝美麗 2001 鄭秀⽂ Sammi Cheng 陳輝陽 Keith Chan 林夕 Lin Xi C0105 痛愛 2001 容祖兒 Joey Yung 陳輝陽 Keith Chan 黃偉⽂ Wyman Wong C0201 好⼼分⼿ 2002 盧巧⾳ Candy Lo 雷頌德 Mark Lui 黃偉⽂ Wyman Wong C0202 爭氣 2002 容祖兒 Joey Yung 陳輝陽 Keith Chan 林夕 Lin Xi C0203 女⼈之苦 2002 許志安 Andy Hui 陳輝陽 Keith Chan 林夕 Lin Xi C0204 愛不釋⼿ 2002 李克勤 Hacken Lee 陳輝陽 Keith Chan 林夕 Lin Xi C0205 明年今⽇ 2002 陳奕迅 Eason Chan 陳⼩霞 Salsa Cheng 林夕 Lin Xi C0301 七友 2003 梁漢⽂ Edmond Leung 雷頌德 Mark Lui 林夕 Lin Xi C0302 我的驕傲 2003 容祖兒 Joey Yung 陳光榮 Kwong Wing Chan 黃偉⽂ Wyman Wong C0303 ⼗⾯埋伏 2003 陳奕迅 Eason Chan Eric Kwok 黃偉⽂ Wyman Wong C0304 我不會唱歌 2003 李克勤 Hacken Lee Edmond Tsang 黃偉⽂ Wyman Wong C0305 可惜我是⽔瓶座 2003 楊千嬅 Miriam Yeung 雷頌德 Mark Lui 黃偉⽂ Wyman Wong 98 ID Song Title Year Singer Composer Lyricist C0401 ⼩城⼤事 2004 楊千嬅 Miriam Yeung 雷頌德 Mark Lui 林夕 Lin Xi C0402 空中⾶⼈ 2004 李克勤 Hacken Lee 伍仲衡 Harry Ng 李克勤 Hacken Lee C0403 世上只有 2004 容祖兒 Joey Yung 陳光榮 Kwong Wing Chan 黃偉⽂ Wyman Wong C0404 愛與誠 2004 古巨基 Leo Ku 曹雪芬 Suet-fun Tso 林夕 Lin Xi C0405 嫁妝 2004 陳慧琳 Kelly Chen 陳光榮 Kwong Wing Chan 黃偉⽂ Wyman Wong C0501 夕陽無限好 2005 陳奕迅 Eason Chan Eric Kwok 林夕 Lin Xi C0502 天才與⽩痴 2005 古巨基 Leo Ku 張佳添 Clayton Cheung, 鄭汝森 Anthony Cheng 林夕 Lin Xi C0503 情非⾸爾 2005 李克勤 Hacken Lee 伍仲衡 Harry Ng 李克勤 Hacken Lee C0504 烈女 2005 楊千嬅 Miriam Yeung 雷頌德 Mark Lui 林夕 Lin Xi C0505 無賴 2005 鄭中基 Ronald Cheng 李峻⼀ Joe Lei 李峻⼀ Joe Lei C0601 愛得太遲 2006 古巨基 Leo Ku 楊鎮邦 Bryan Yeung 林夕 Lin Xi C0602 紅綠燈 2006 鄭融 Stephanie Cheng 張家誠 Alan Cheung 陳少琪 Keith Chan C0603 華麗邂逅 2006 容祖兒 Joey Yung Eric Kwok 黃偉⽂ Wyman Wong C0604 最佳損友 2006 陳奕迅 Eason Chan Eric Kwok 黃偉⽂ Wyman Wong C0605 富⼠⼭下 2006 陳奕迅 Eason Chan Christopher Chak 林夕 Lin Xi C0701 愛回家 2007 古巨基 Leo Ku Dick Lee 林夕 Lin Xi C0702 男⼈ KTV 2007 側⽥ Justin Lo 殷⽂琦 Philip Yin, 蔡政勳 Andy Tsai, 胡彥斌 Tiger Hu 林夕 Lin Xi, 何啟弘 Chi Hung He, 甄健強 Kin Yan C0703 花落誰家 2007 李克勤 Hacken Lee Eric Kwok 林若寧 Riley Lam C0704 逼得太緊 2007 吳雨霏 Kary Ng 黃丹儀 Dennie Wong 林夕 Lin Xi C0705 ⽊紋 2007 何韻詩 Denise Ho 張繼聰 Louis Cheung 黃偉⽂ Wyman Wong C0801 撈⽉亮的⼈ 2008 楊千嬅 Miriam Yeung 陳台證 Taz Tan 林若寧 Riley Lam 99 ID Song Title Year Singer Composer Lyricist C0802 囍帖街 2008 謝安琪 Kay Tse Eric Kwok 黃偉⽂ Wyman Wong C0803 愛不疚 2008 林峯 Raymond Lam 鄧智偉 Chi Wai Tang 張美賢 Sandy Cheung C0804 櫻花樹下 2008 張敬軒 Hins Cheung 伍卓賢 Cheuk Yin Ng 林若寧 Riley Lam C0805 跑步機上 2008 容祖兒 Joey Yung 王雙駿 Carl Wong 黃偉⽂ Wyman Wong C0901 地球很危險 2009 古巨基 Leo Ku John Laudon 林夕 Lin Xi C0902 你瞞我瞞 2009 陳柏宇 Jason Chan 陳光榮 Kwong Wing Chan 林夕 Lin Xi C0903 原來過得很快樂 2009 楊千嬅 Miriam Yeung 伍仲衡 Harry Ng 林夕 Lin Xi C0904 給⾃⼰的信 2009 鍾舒漫 Sherman Chung Angela Aki 周耀輝 Yiu Fai Chow C0905 年度之歌 2009 謝安琪 Kay Tse Christopher Chak 黃偉⽂ Wyman Wong C1001 愛的習慣 2010 側⽥ Justin Lo 雷頌德 Mark Lui 林夕 Lin Xi C1002 破相 2010 容祖兒 Joey Yung 陳輝陽 Keith Chan 黃偉⽂ Wyman Wong C1003 陀⾶輪 2010 陳奕迅 Eason Chan Vincent Chow 黃偉⽂ Wyman Wong C1004 SimpleLoveSong 2010 RubberBand 阿正 Bonnie Wong Tim Lui C1005 天梯 2010 C AllStar 賴映彤 Edwina Lai 鍾晴 Wendy Chung C1101 末⽇ 2011 王菀之 Ivana Wong 王菀之 Ivana Wong 黃偉⽂ Wyman Wong C1102 牆紙 2011 容祖兒 Joey Yung ⽅⼤同 Khalil Fong 黃偉⽂ Wyman Wong C1103 年年 2011 蔡卓妍 Charlene Choi Eric Kwok 林若寧 Riley Lam C1104 戀上外星⼈ 2011 張智霖 Julian Cheung Kim Bo Min 火火 Fire Lee C1105 花千樹 2011 容祖兒 Joey Yung Mattew Tisher, Andrew Ang 黃偉⽂ Wyman Wong C1201 留⽩ 2012 王菀之 Ivana Wong 常⽯磊 Shilei Chang 林夕 Lin Xi C1202 戀無可戀 2012 古巨基 Leo Ku ⽅皓玟 Chaimaine Fong 林夕 Lin Xi C1203 昨天 2012 Mr. Mr. 劉卓輝 Gene Lau, Mr. 100 ID Song Title Year Singer Composer Lyricist C1204 ⽩頭到老 2012 蔡卓妍 Charlene Choi Eric Kwok 林若寧 Riley Lam C1205 重新長⼤ 2012 許廷鏗 Alfred Hui 伍樂城 Ronald Ng 許廷鏗 Alfred Hui, Kennedy 7, 曾紀諾 Brian Tsang C1301 天窗 2013 容祖兒 Joey Yung 周柏豪 Pakho Chau 黃偉⽂ Wyman Wong C1302 青春頌 2013 許廷鏗 Alfred Hui 藍奕邦 Pong Nan 藍奕邦 Pong Nan C1303 任我⾏ 2013 陳奕迅 Eason Chan Christopher Chak 林夕 Lin Xi C1304 最好的時刻 2013 謝安琪 Kay Tse Cousin Fung 周博賢 Adrian Chow C1305 哥歌 2013 王菀之 Ivana Wong 王菀之 Ivana Wong 王菀之 Ivana Wong C1401 獨家村 2014 謝安琪 Kay Tse Christopher Chak 林夕 Lin Xi C1402 青春常駐 2014 張敬軒 Hins Cheung 張敬軒 Hins Cheung, Johnny Yim 黃偉⽂ Wyman Wong C1403 流淚⾏勝利道 2014 許志安 Andy Hui Larry Wong 周耀輝 Yiu Fai Chow C1404 ⾼⼭低⾕ 2014 林奕匡 Phil Lam 林奕匡 Phil Lam 陳詠謙 Abrahim Chan C1405 越難越愛 2014 吳若希 Jinny Ng 徐洛鏘 Damon Chui 張美賢 Sandy Cheung C1501 找對的⼈ 2015 張敬軒 Hins Cheung Iki 林若寧 Riley Lam C1502 我們都是這樣長⼤的 2015 林欣彤 Mag Lam 林欣彤 Mag Lam 林若寧 Riley Lam C1503 無條件 2015 陳奕迅 Eason Chan Eric Kwok 袁兩半 Calvin Poon C1504 逾越⽣死 2015 C AllStar Cousin Fung 鍾晴 Wendy Chung C1505 過客別墅 2015 張敬軒 Hins Cheung Vincent Chow 林夕 Lin Xi C1601 女神 2016 鄭欣宜 Joyce Cheng 藍奕邦 Pong Nan 黃偉⽂ Wyman Wong C1602 無⼈知道雙⼦座 2016 容祖兒 Joey Yung Cousin Fung 黃偉⽂ Wyman Wong C1603 百姓 2016 吳業坤 James Ng Larry Wong 黃偉⽂ Wyman Wong C1604 我的志願 2016 許廷鏗 Alfred Hui 陳光榮 Kwong Wing Chan 林夕 Lin Xi 101 ID Song Title Year Singer Composer Lyricist C1605 ⽭盾⼀⽣ 2016 JW 林家謙 Terence Lam 陳詠謙 Abrahim Chan C1701 失魂記 2017 李克勤 Hacken Lee 馮翰銘 Alex Fung 林若寧 Riley Lam C1702 長相廝守 2017 ToNick ToNick 梁栢堅 Pak Kin Leung, 薑檸樂 GingerLemonCola C1703 天網 2017 周柏豪 Pakho Chau 張家誠 Alan Cheung 張美賢 Sandy Cheung C1704 天敵 2017 衛蘭 Janice Vidal JUDE 黃偉⽂ Wyman Wong C1705 霸氣情歌 2017 陳柏宇 Jason Chan 林奕匡 Phil Lam 黃偉⽂ Wyman Wong C1801 老少平安 2018 周柏豪 Pakho Chau 藍奕邦 Pong Nan 藍奕邦 Pong Nan C1802 認真如初 2018 陳柏宇 Jason Chan Cousin Fung 陳詠謙 Abrahim Chan C1803 ⼀個女⼈和浴室 2018 謝安琪 Kay Tse Bert 黃偉⽂ Wyman Wong C1804 停半分鐘聽⼀闋歌 2018 許廷鏗 Alfred Hui Cousin Fung, 黃兆銘 Nick Wong 6號 Hou Cheong Mau C1805 百年樹⽊ 2018 張敬軒 Hins Cheung 伍卓賢 Cheuk Yin Ng 林若寧 Riley Lam C1901 我們與愛的距離 2019 許廷鏗 Alfred Hui Cousin Fung, 黃兆銘 Nick Wong 林夕 Lin Xi C1902 最後的信仰 2019 林⼆汶 Eman Lam 藍奕邦 Pong Nan 林夕 Lin Xi C1903 我們都是這樣長⼤的 2019 鄭秀⽂ Sammi Cheng 徐沛昕 Jessica Tsui 詩詞 Sze Man Chan C1904 2084 2019 Dear Jane Howie 林寶 Bo Lam C1905 讓愛⾼⾶ 2019 周柏豪 Pakho Chau 張家誠 Alan Cheung 張美賢 Sandy Cheung C2001 呼吸有害 2020 莫⽂蔚 Karen Mok 鄧智偉 Chi Wai Tang 羅健成 Jiancheng Luo C2002 感情這回事 2020 陳柏宇 Jason Chan 佳旺 Keon Chia 陳詠謙 Abrahim Chan C2003 劫後餘⽣ 2020 周柏豪 Pakho Chau 徐繼宗 Jone Chui 陳詠謙 Abrahim Chan C2004 無⼒感 2020 許廷鏗 Alfred Hui 陳考威 Gareth Chan T-rexx C2005 銀河修理員 2020 Dear Jane Howie 黃偉⽂ Wyman Wong 102 Appendix B: Count of bigram types with all combinations of speech melodies and song melodies Down Level Up-12 -11 -10 -9 -8 -7 -6 -5 -4 -3 -2 -1 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 Grand TotalDown 39 7 28 112 152 432 12 535 812 1,257 4,062 1,683 159 41 136 18 30 6 # - - - - 2 - # # 9,523 T1–T3 2 # 1 7 5 47 # 40 273 20 1,258 11 9 - 1 1 - - # - - - - # - # # 1,675 T1–T4 22 7 8 63 26 155 # 60 5 2 17 - 6 - 1 - - - # - - - - # - # # 372 T1–T5 1 # 1 2 2 21 # 30 152 14 739 6 16 - - 1 - - # - - - - # - # # 985 T1–T6 6 # 6 2 34 56 4 127 1 196 17 8 22 - 9 - - - # - - - - # - # # 488 T2–T3 # # 1 3 ` 23 # 11 116 3 575 3 6 - 1 - - - # - - - - # - # # 745 T2–T4 2 # 2 25 11 52 # 22 6 1 14 - - - 1 - - - # - - - - # - # # 136 T2–T5 # # # 1 - 9 # 19 63 1 421 3 5 - - 1 - - # - - - - # - # # 523 T2–T6 3 # 4 - 26 15 8 57 2 72 6 7 3 - 9 - - - # - - - - # - # # 212 T3–T4 1 # 1 - 18 26 # 99 8 95 28 23 25 - 36 - 2 - # - - - - # - # # 362 T3–T6 # # # - 3 - # 1 7 435 86 887 5 - 21 - 14 - # - - - - # - # # 1,459 T5–T4 2 # 4 3 22 18 # 67 2 117 2 30 26 1 46 - 3 - # - - - - # - # # 343 T5–T6 # # # - 2 - # 1 2 297 38 688 12 - 4 - 11 - # - - - - 2 - # # 1,057 T6–T4 # # # 6 - 10 # 1 175 4 861 17 24 40 7 15 - 6 # - - - - # - # # 1,166 Level # # # - 2 6 # 99 48 317 1,914 936 5,969 180 984 136 35 24 # 8 - 5 - # - # # 10,663 T1–T1 # # # - 2 3 # 53 14 139 812 423 1,194 22 45 14 - 2 # - - - - # - # # 2,723 T1–T2 # # # - - 3 # 16 11 99 442 218 450 6 21 3 - - # - - - - # - # # 1,269 T2–T1 # # # - - - # 15 9 49 335 154 511 39 82 4 - 3 # - - - - # - # # 1,201 T2–T2 # # # - - - # 10 5 16 168 66 218 4 14 2 - - # - - - - # - # # 503 T3–T3 # # # - - - # 2 - 2 13 26 720 2 113 - 5 3 # - - - - # - # # 886 T3–T5 # # # - - - # 1 - 2 3 6 441 1 101 1 2 1 # - - - - # - # # 559 T4–T4 # # # - - - # - 9 1 36 4 686 85 295 100 21 10 # 3 - 5 - # - # # 1,255 T5–T3 # # # - - - # 2 - 7 2 32 470 1 118 - 3 - # - - - - # - # # 635 T5–T5 # # # - - - # - - 2 1 1 369 1 96 - - 1 # - - - - # - # # 471 T6–T6 # # # - - - # - - - 102 6 910 19 99 12 4 4 # 5 - - - # - # # 1,161 Up # # # - - - # - - 12 25 35 67 2,343 4,332 1,491 646 805 15 699 182 272 125 43 182 5 17 11,296 T3–T1 # # # - - - # - - 1 3 16 13 44 947 27 178 27 1 25 - 4 - # - # # 1,286 T3–T2 # # # - - - # - - 2 2 4 8 15 471 1 76 4 1 10 - 4 - # - # # 598 T4–T1 # # # - - - # - - - - - - - 4 7 2 56 3 209 27 115 46 24 112 # 16 621 T4–T2 # # # - - - # - - - - - - 1 - 15 3 25 # 114 6 82 22 5 48 # 1 322 T4–T3 # # # - - - # - - - - - - 2 14 115 7 174 # 71 63 5 25 # 4 # # 480 T4–T5 # # # - - - # - - - - - - - 2 77 - 156 # 50 38 8 13 # 16 # # 360 T4–T6 # # # - - - # - - - - - 2 15 1,432 21 177 39 # 34 - 38 - 9 - # # 1,767 T5–T1 # # # - - - # - - 5 1 13 17 32 758 32 138 49 # 34 - 10 3 5 - # # 1,097 T5–T2 # # # - - - # - - 4 1 2 6 11 468 1 60 19 # 21 - 3 - # - # # 596 T6–T1 # # # - - - # - - - 13 - 2 176 18 279 2 134 8 85 23 2 11 # 1 2 # 756 T6–T2 # # # - - - # - - - 3 - 4 94 4 127 3 112 2 36 10 1 3 # 1 1 # 401 T6–T3 # # # - - - # - - - 1 - 8 1,038 114 384 - 5 # 6 12 - - # - 2 # 1,570 T6–T5 # # # - - - # - - - 1 - 7 915 100 405 - 5 # 4 3 - 2 # - # # 1,442 Grand Total 39 7 28 112 154 438 12 634 860 1,586 6,001 2,654 6,195 2,564 5,452 1,645 711 835 15 707 182 277 125 45 182 5 17 31,482 Direction and interval size of song melody (semitone)Direction and tone combination of speech melody
Thesis/Dissertation
eng
Music - Theory
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
VanHandel, Leigh
Law, Hedy
A corpus study of tone-melody correspondence in Cantopop, 2000–2020
Text