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Now you hear it, now you don't: Vowel devoicing in Japanese infant-directed speech*

Published online by Cambridge University Press:  03 June 2009

LAUREL FAIS ,
SACHIYO KAJIKAWA ,
SHIGEAKI AMANO  and
JANET F. WERKER
LAUREL FAIS*
Affiliation:
Department of Psychology, University of British Columbia, Vancouver, Canada
SACHIYO KAJIKAWA
Affiliation:
Tamagawa University Research Institute, Tamagawa University, Tokyo, Japan
SHIGEAKI AMANO
Affiliation:
NTT Communication Science Laboratories, NTT Corporation, Kyoto, Japan
JANET F. WERKER
Affiliation:
Department of Psychology, University of British Columbia, Vancouver, Canada
*
Address for correspondence: Laurel Fais, 2136 West Mall, Vancouver, BC, V6T 1Z4, Canada. e-mail: [email protected].
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Abstract

In this work, we examine a context in which a conflict arises between two roles that infant-directed speech (IDS) plays: making language structure salient and modeling the adult form of a language. Vowel devoicing in fluent adult Japanese creates violations of the canonical Japanese consonant–vowel word structure pattern by systematically devoicing particular vowels, yielding surface consonant clusters. We measured vowel devoicing rates in a corpus of infant- and adult-directed Japanese speech, for both read and spontaneous speech, and found that the mothers in our study preserve the fluent adult form of the language and mask underlying phonological structure by devoicing vowels in infant-directed speech at virtually the same rates as those for adult-directed speech. The results highlight the complex interrelationships among the modifications to adult speech that comprise infant-directed speech, and that form the input from which infants begin to build the eventual mature form of their native language.

Type
Articles
Information
Journal of Child Language , Volume 37 , Issue 2 , March 2010 , pp. 319 - 340
Copyright
Copyright © Cambridge University Press 2009

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Footnotes

[*]

The authors would like to thank Tomoko Kawaguchi for transcribing the data, Lorella Chan, Nozomi Kido, Amber Lo and Nicole Stringer for their hard work in coding the data, and Tracy Cassells for assistance with statistical analysis.

References

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