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Sarah Bakst, UC Berkeley Phonetics and Phonology in Europe University of Cambridge June 29, 2015
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Retroflexes and Dentals 210 ms -1 kHz- -2 kHz- -3 kHz- -4 kHz- -5 kHz- a ɖ a a d ̪ a 210 ms
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Burst spectra retroflex dental
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Different distributions HindiTamil word-initial ɖ ar ‘fear’ *word-initial (except borrowings) word-final pe ʈ ‘stomach’; pe ɽ ‘tree’ word-final (resonants) p ɔɳ ‘girl’ word-medial lə ɖː u ‘ladoo’ (type of sweet) word-medial a ːɖɨ ‘sheep’
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Hypothesis Perceptual effect ~ phonological pattern? a. Tamil speakers will be less sensitive to burst cues than Hindi speakers. b. Tamil speakers will be more sensitive to vowel transitions that Hindi speakers. Effect not predicted by motor theory (Liberman 1985) and some versions of direct realism (e.g. Fowler 1986).
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Stimuli Recordings of Hindi and Tamil speakers Isolation of a ɖ a and ad ̪ a sequences Cross-language and speaker comparison Retroflex Dental
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Synthesis Synthesis of a ɖ a and ad ̪ a using the Klatt synthesizer Equalized pitch Interpolated seven step continuum between the two stops. Five continua with altered cues
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Synthesized Stimuli Vowel cues only (VC), no burst. Burst cues only (CV), no initial vowel. Ambiguous burst: VC + step 4 burst. Ambiguous vowel: step 4 vowel transition + CV Mismatch: step 1 vowel + step 7 burst -> step 7 vowel + step 1 burst
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Procedure Two-alternative forced-choice identification task in Open Sesame in sound-attenuating booth All stimuli combined and randomized Ten repetitions of all stimuli (420 trials total) Break given just over halfway through Experiment lasted about twenty minutes
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Procedure
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Participants Mostly UC Berkeley students, some members of the community Native speakers of Hindi (16) or Tamil (17) $5 or extra credit in intro linguistics class
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Modeling Mixed-effects logistic model in R to predict probability of “retroflex” response. One model for each continuum: response ~ step*language + 1|sub
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Results p-level: 0.0083 after Bonferroni corrections Trending overall language effect: CV (p =.017) Interaction on particular steps: baseline (p =.04, marginal) VC (p =.017) ambiguous consonant (p =.0001) mismatch condition (p <.0001)
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† † * * * * *
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Interpretation Tamil speakers slightly more sensitive to burst cues Hindi speakers slightly more sensitive to vowel cues Opposite of specific prediction
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Discussion Differences in number and type of phonotactic systems Frequency of contrast and functional load
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Conclusion Small effect of language experience on sensitivity to different acoustic cues Phonetic knowledge is learned rather than innate. Intended gesture unlikely to be the object of perception
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Acknowledgments Many thanks to Prof. Keith Johnson for supervising the project Prof. Beth Hume Emily Cibelli, Clara Cohen, Andréa Davis, and other members of the UC Berkeley Phonology Lab Undergraduate assistants Shannon Foster and Akshayraj Aitha for running subjects and the Linguistics Research Apprenticeship Program for funding the project
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Selected References Best C. T. (1995). A direct realist view of cross-language speech perception, in Speech Percep- tion and Linguistic Experience: Issues in Cross-Language Research, ed Strange W., editor. (Timonium, MD: York Press; ), 171–204. Fowler, C.A. (2006) Compensation for coarticulation reflects gesture perception, not spectral contrast. Percept. & Psychophys. 68(2), 161–177. Gerrits, E., and M. E. H. Schouten. 2004. Categorical perception depends on the discrimination task. Perception & Psychophysics 66:363–376. Holt, Lori L., and Andrew J. Lotto. 2006. Cue weighting in auditory categorization: Implica- tions for first and second language acquisition. Journal of the Acoustical Society of America 119:3059–3071. Klatt, Dennis H. 1980. Software for a cascade/parallel formant synthesizer. Journal of the Acoustical Society of America 67:971–995. Liberman, Alvin M., and Ignatius G. Mattingly. 1985. The motor theory of speech perception revised. Cognition 1–36. Lisker, Leigh. 1986. “Voicing” in English: A catalogue of acoustic features signaling /b/ versus /p/ in trochees. Language and Speech 29:3–11. Mathoˆt, S., D. Schreij, and J. Theeuwes. 2012. OpenSesame: An open-source, graphical exper- iment builder for the social sciences. Behavior Research Methods 44:314–324. Morrison, Geoffrey Stewart, and Maria V. Kondaurova. 2009. Analysis of categorical response data: Use logistic regression rather than endpoint-difference scores or discriminant analysis (L). Journal of the Acoustical Society of America 126:2159–2162. Steriade, Donca. 2001. Directional asymmetries in place assimilation: a perceptual account. In Perception in phonology, ed. E. Hume and K. Johnson. Academic Press. Stevens, Kenneth N., and Sheila E. Blumstein. 1975. Quantal aspects of consonant production and perception: a study of retroflex stop consonants. Journal of Phonetics 3:215–233.
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Palatography Tamil Hindi Tamil
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