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The syllable as a prosodic unit in Japanese lexical strata: evidence from text-setting Rebecca L Starr National University of Singapore Stephanie S Shih University of California, Merced LabPhon 14 National Institute for Japanese Linguistics 25 27 July 2014 Un- der the sea su- ba- ra- shii 1

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The Mora in Japanese Japanese = prototypical example of a mora-based language e.g., kai.zen = [ka] [i] .[ze] [n] o Rhythmic timing depends on mora units (Homma 1981; Port et al. 1987; cf., Beckman 1982) o Phonological/morphological implications: e.g., accent placement, compensatory lengthening o Traditional Japanese poetry = mora counting e.g., haiku 5 7 5 mora form 2

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Syllable usually treated as unnecessary or unimportant in Japanese phonology (Labrune 2012). Kubozono (1999; et seq.) : Japanese is (in part) a syllable-based language. o accent placement, word formation, etc. The Syllable in Japanese? 3

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Labrune (2012): no positive psycholinguistic evidence for the cognitive reality of the syllable in Japanese. The Syllable in Japanese? 4

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Major lexical strata in Japanese (It and Mester 1999) : Yamato (native Japanese) Ex: suki (to like) Sino-Japanese (Chinese origin) Ex: ningen (human) Foreign (~85% English origin) Ex: benchi (bench) Mimetic Ex: fuwafuwa (fluffy) Lexical Strata in Japanese 5

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Strata characterized by different phonotactics, and phonological rules (It and Mester 1999). o e.g., long a never occurs in Sino-Japanese words. Because Chinese and English are syllable-based, is it possible that the syllable is a more salient unit in the Sino and Foreign strata? Alternatively, does widespread knowledge of English contribute to increased salience of the syllable in just the Foreign stratum? Lexical Strata in Japanese 6

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Text-setting: the pairing of language and music in song. Typologically, text-setting makes use of salient prosodic units particular to a language. o English: syllables, lexical and phrasal stresses (Halle & Lerdhal 1993; Shih 2008; Hayes 2009; a.o.) o Cantonese: tonal melodies matched in musical melodies (Yung 1991) Similar claims for metrical typology (Hanson and Kiparksy 1996) Evidence from Text-Setting 7

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Japanese text-setting: Claimed to operate as a mora-based system (Kubozono 1999; Hayes and Swiger 2008; cf. Manabe 2009) = each mora must receive (at least) one note. e.g., do.ra.go-n bo-o.ru (Dragonball Z theme, 1989) x x x x x x x = 7 notes Evidence from Text-Setting 8

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BUT, multi-moraic notes show up frequently in modern Japanese songs. Similar findings in poetry (Tanaka 2012) In these settings, it is the syllable that receives at least one note. e.g., do- ra- gon boo-ru x x x x x = 5 notes Evidence from Text-Setting 9

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What constraints govern moraic vs. non- moraic text-setting variation in Japanese? Do Japanese listeners perceive the syllable as an acceptable segmentation unit in text- setting? o Is it as acceptable as the mora? Main Research Questions 10

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Moraic vs. syllabic treatments in Japanese text- setting are conditioned by lexical, phonological, and stylistic constraints. o Strata in the Japanese lexicon o Information density o Phonological factors (e.g., sonority) o Stylistic factors (e.g., musical genre) Japanese listeners fully accept syllable-based text-setting. o Particularly when a moraic setting is impractical. Main Claims 11

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Corpus study Experiment (prelim. results) Two Approaches 12

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Three corpora of Japanese songs compared: Corpus Study Anime theme songsnativeLate 1980s 90s Disney songstranslatedLate 1980s 90s Christmas songstranslatedLate 19 th c. 21 st c. 13

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Four Variables Coda-N Vi (ai, ui, ei, oi) Long Vowels Inter-voiceless-consonant i and u 14

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Example Moraic Syllabic ningen (human)ni-n-ge-nnin-gen sekai (world) se-ka-i se-kai hoshii (want)ho-shi-i ho-shii suki (like)s-ki, s-kis( )ki Example settings 15

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Santa appears in moraic and syllabic settings within the same song: sa n ta no o ji sa n ga de mo so no san ta wa (I Saw Mommy Kissing Santa Claus, 1952, trans. 1962) Example Clip 16

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Results: Difference by lexical stratum Coda-N ViLong Vowels Inter-voiceless i and u 17 Syllabic Moraic

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Results: Differences by corpus 18

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Results: Regression modeling o Generalized linear mixed-effect model (glmer). o Significantly more syllabic settings in translated song corpora than native corpus. o Significantly more syllabic settings in Foreign stratum words. o No reliable difference between Sino and Yamato strata words. o Other phonological factors also significant for certain variables: e.g., sonority scale for diphthongs (e.g., ai vs. ei; Prince 1983) 19

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Syllabic text-setting is present in both translated and native corpora, but is more common in translated corpora. Foreign stratum words use significantly less moraic text-setting. Certain phonological contexts encourage syllabic text-setting (e.g., preferred consonant clusters, decreasing sonority). Summary of Results 20

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Experiment Corpus study demonstrates that trained composers use both moraic and syllabic settings and prefer to use syllabic settings for Foreign stratum words. Do ordinary Japanese speakers follow the same patterns? What about Japanese learners? Perceptual experiment to test acceptability of different text-setting styles. 21

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Novel methodology: Vocaloid Creating stimuli involving multiple sung arrangements presents a challenge. We used Yamahas Vocaloid 3 software, which produces synthesized sung Japanese. 22 sakura

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Factors Linguistic variables: Coda-N Vi (limited to ai) Strata: Foreign vs. Sino Not possible to make minimal pairs with Yamato Selected near-minimal pairs. Ex: benchi / bengi 23

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Factors Settings tested: Mora: mi-n-to da-yo Syllable:min-to da-yo-ne Split Syllable(melisma):mi-in-to da-yo Bad 1 (too small):m-in-to da-yo Bad 2 (too large):mi-i-i-i-intodayo 24

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Predictions Native Japanese will prefer Syll. to Split-Syll. Syllabic: (min-to da-yo-ne) 6 moras for only 5 notes. Since there is no moraic solution, listeners will be okay with syllabic. Split-syllabic: (mi-in-to da-yo) 5 moras for 5 notes, but arrangement is non-moraic anyway. Turns short vowel into long vowel. Listeners will prefer both syllable-based settings over the bad settings, which do not correspond to any proposed salient prosodic unit. 25

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Methodology Motsu-kun is learning to arrange lyrics to a melody. Help him improve by rating his work! (minto dayone) Asked to rate on 1-4 Likert scale. 26

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Participants & Implementation 18 native Japanese speakers Asked for frequency of English use 10 Japanese learners (Eng & Chi native spkrs) Asked for length of Japanese study Survey conducted online using Qualtrics. Still recruiting participants: http://bit.ly/1oblYNz http://bit.ly/1oblYNz Data analyzed using lmer (linear mixed-model regression) in R. 27

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Findings 28

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Key Findings Native speakers rated Syllabic (min-to) just as highly as Moraic setting (mi-n-to). Split-Syll. (mi-in-to) was rated significantly lower than Syll., but significantly higher than Bad1 or Bad2. Conclusions: o Native listeners prefer a one-to-one correspondence between note and prosodic unit, whether mora or syllable. o When there is room in the melody for a moraic setting, syllable-based is dispreferred, but not totally rejected. 29

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Key Findings Japanese learners rate Moraic, Syll., and Split-Syll. settings as equally good. Moraic settings, which do not occur in English and Chinese, are just as highly rated as familiar syllable- based settings. Learners must be acquiring familiarity with moraic segmentation as part of the Japanese learning process. But learners do not pick up that Split-Syll (mi-in-to) is dispreferred. Not as sensitive to vowel length? Dont care about one-to-one match between notes and prosodic unit? 30

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Key Findings Trend, but no significant differences between Foreign and Sino strata (contrary to corpus findings). No effects of English exposure or whether currently living in Japan. More participants needed. 31

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Conclusions: Experiment Positive evidence for the cognitive reality of the syllable in Japanese: Japanese listeners fully accept syllable-based segmentation in contexts where moraic segmentation is impractical. When moraic segmentation is available, syllable- based segmentation is dispreferred, but rated more highly than settings which segment along non-salient prosodic boundaries. 32

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Overall Conclusions Both syllabic and moraic text-setting styles are prevalent and acceptable in Japanese. Text-setting style is conditioned by factors such as phonological context and (possibly) lexical stratum. Native listeners prefer a one-to-one correspondence between notes and prosodic units, whether mora or syllable. 33

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Acknowledgements to Noriko Manabe, Reiko Kataoka, Roey Gafter, Junko Ito, Mie Hiramoto, Yosuke Sato, Sakiko Kajino, Nala Lee, and Jason Ginsburg for their input and assistance. . contact: rstarr@nus.edu.sg shih@ucmerced.edu Thank you! 34

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Beckman, Mary. 1982. Segment Duration and the 'Mora' in Japanese. Phonetica. 39. 113-135. Halle, John and Fred Lerdahl. 1993. A Generative Text-setting Model. Current Musicology. 55: 3-21. Hanson, Kristin and Paul Kiparsky. 1996. A Parametric Theory of Poetic Meter. Language. 72(2). 287-335. Hayes, Bruce. 2009. Textsetting as Constraint Conflict. In Jean-Louis Aroui and Andy Arleo (ed). Towards a Typology of Poetic Forms: From language to metrics and beyond. Amsterdam: John Benjamins. 43-62. Hayes, Bruce and Tami Swiger. 2008. Two Japanese Childrens Songs. MS. University of California, Los Angeles. 12 pages. Homma, Yayoi. 1981. Durational relationship between Japanese stops and vowels. Journal of Phonetics 9 (3): 273 281. It, Junko & Armin Mester. 1999. Japanese Phonology. In John Goldsmith (ed). The Handbook of Phonological Theory. Oxford: Wiley-Blackwell. 818-838. Kubozono, Haruo. 1999. Mora and Syllable. In Natsuko Tsujimura (ed). The Handbook of Japanese Linguistics. Oxford: Wiley-Blackwell. 31-61. Labrune, Laurence. 2012. Questioning the universality of the syllable: evidence from Japanese. Phonology 29:1, 113 - 152. Manabe, Noriko. 2009.Western Music in Japan: The evolution of styles in childrens songs, hip-hop, and other genres. Ph.D. dissertation, CUNY Graduate Center. Pellegrino, Francois, Coupe, Christophe, and Egidio Marsico. 2011. A Cross-Language Perspective on Speech Information Rate. Language. 87(3). 539 558. Port, Robert. F., Dalby, Jonathan & O'Dell, Michael. (1987). Evidence for mora-timing in Japanese. Journal of the Acoustical Society of America. 81. 1574 1585. Prince, Alan. 1983. Relating to the Grid. Linguistic Inquiry. 11:511-562. Shih, Stephanie. 2008. Text-Setting: a (musical) analogy to poetic meter. Paper presented at New Research Programs in the Linguistics of Literature. University of California, Berkeley. Tanaka, Shinichi. 2012. Syllable Neutralization and Prosodic Unit in Japanese Senryu Poems. Paper presented at Metrics, Music and Mind. Rome, Italy. Yung, Bell. 1991. The Relationship of Text and Tune in Chinese Opera. In J. Sundberg; L. Nord; and R. Carlson (ed). Music, Language, Speech, and Brain. London: Macmillan. 408-418. Select references 35

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11 songs total: o Totoro (1988) o Dragonball Z (1989) o Kikis Delivery Service (1989) o All-Purpose Cultural Cat-Girl Nuku Nuku (1990) o Gundam F91 (1991) o Bubblegum Crash (1991) o Slayers (1995) o Sailor Moon (1995) o Tenchi Universe (1995) o Slayers Next (1996) o Boys Before Flowers (1996) Anime Corpus 36

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Films: o The Little Mermaid (1989 translation) o Beauty and the Beast (1991) o Aladdin (1992) o The Lion King (1994) o The Little Mermaid (1997 translation) 17 songs total Disney Corpus 37

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10 songs total: Hark the Herald Angels Sing (1888) O Holy Night (1909) Silent Night (1909) Jingle Bells (1958) Santa Claus is Coming to Town (1959) Rudolph the Red-Nosed Reindeer (1959) I Saw Mommy Kissing Santa Claus (1962) Winter Wonderland (1962) The Christmas Song (1996) We Wish You a Merry Christmas (2005) Christmas Corpus 38

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Excluded: o Code-switching involving two or more consecutive words in English with different parts of speech. o Ex: Its my day o Content that was spoken rather than sung. o Discourse particles like aa. o Nonsense words for which a stratum could not be determined. o Mimetic stratum words (not enough for analysis). Coding Methodology 39

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Native speakers LMER REML criterion at convergence: 422.5 Scaled residuals: Min 1Q Median 3Q Max -2.12822 -0.70806 -0.07082 0.59577 2.71389 Random effects: Groups Name Variance Std.Dev. participant (Intercept) 0.2245 0.4739 Residual 0.4958 0.7041 Number of obs: 180, groups: participant, 18 Fixed effects: Estimate Std. Error df t value Pr(>|t|) (Intercept) 1.861e+00 1.703e-01 5.663e+01 10.929 1.33e-15 *** settings2 5.556e-01 1.660e-01 1.570e+02 3.347 0.00102 ** settingb1 9.444e-01 1.660e-01 1.570e+02 5.690 6.05e-08 *** settingb2 1.972e+00 1.660e-01 1.570e+02 11.883 < 2e-16 *** settingm -2.778e-01 1.660e-01 1.570e+02 -1.674 0.09619 Experiment: statistical models 40

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Learners LMER REML criterion at convergence: 240.9 Scaled residuals: Min 1Q Median 3Q Max -2.3779 -0.7192 0.0632 0.5096 2.3131 Random effects: Groups Name Variance Std.Dev. participant (Intercept) 0.1830 0.4278 Residual 0.5378 0.7334 Number of obs: 100, groups: participant, 10 Fixed effects: Estimate Std. Error df t value Pr(>|t|) (Intercept) 1.7555 0.2375 42.1900 7.391 3.92e-09 *** settingb1 0.7500 0.2319 83.9900 3.234 0.00175 ** settingb2 1.7238 0.2339 84.0200 7.369 1.09e-10 *** settingm -0.1369 0.2324 84.0000 -0.589 0.55744 settings2 0.2131 0.2324 84.0000 0.917 0.36181 stratsino 0.1200 0.1467 83.9900 0.818 0.41560 Experiment: statistical models 41