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Prosodic disambiguation of noun/verb homophones in child-directed speech*

Published online by Cambridge University Press:  02 March 2016

ERIN CONWELL
ERIN CONWELL*
Affiliation:
North Dakota State University
*
Address for correspondence: Erin Conwell, North Dakota State University, NDSU Dept. 2765, P.O. Box 6050, Fargo, ND 58108-6050. tel: 1-701-231-6123; e-mail: [email protected]
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Abstract

One strategy that children might use to sort words into grammatical categories such as noun and verb is distributional bootstrapping, in which local co-occurrence information is used to distinguish between categories. Words that can be used in more than one grammatical category could be problematic for this approach. Using naturalistic corpus data, this study asks whether noun and verb uses of ambiguous words might differ prosodically as a function of their grammatical category in child-directed speech. The results show that noun and verb uses of ambiguous words in sentence-medial positions do differ from one another in terms of duration, vowel duration, pitch change, and vowel quality measures. However, sentence-final tokens are not different as a function of the category in which they were used. The availability of prosodic cues to category in natural child-directed speech could allow learners using a distributional bootstrapping approach to avoid conflating grammatical categories.

Type
Brief Research Reports
Information
Journal of Child Language , Volume 44 , Issue 3 , May 2017 , pp. 734 - 751
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Copyright
Copyright © Cambridge University Press 2016 

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Footnotes

[*]

This research was supported by Grant 1R15HD077519-01 to the author from the National Institute of Child Health and Human Development, which is part of the National Institutes of Health (NIH). The contents of this paper are the sole responsibility of the author and do not necessarily represent the official views of NICHD or NIH. Additionally, I thank Brenden Melvie, Katelyn Tallas, Matthew Kramer, Felix Pichardo, Cheyenne Brady, Adrienne MacDonald, Elisabeth Dukowitz, and Alexandra Howatt for their assistance with the token extraction and measurement, Alejandrina Cristia for sharing her PRAAT scripts, and two anonymous reviewers for their helpful comments on the manuscript.

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