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Implicational markedness and frequency in constraint-based computational models of phonological learning*

Published online by Cambridge University Press:  22 March 2010

GAJA JAROSZ
GAJA JAROSZ*
Affiliation:
Yale University
*
Address for correspondence: Department of Linguistics, Yale University, 370 Temple St., Room 204, P.O. Box 208366, New Haven, CT 06520-8366, USA. Email: [email protected]
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Abstract

This study examines the interacting roles of implicational markedness and frequency from the joint perspectives of formal linguistic theory, phonological acquisition and computational modeling. The hypothesis that child grammars are rankings of universal constraints, as in Optimality Theory (Prince & Smolensky, 1993/2004), that learning involves a gradual transition from an unmarked initial state to the target grammar, and that order of acquisition is guided by frequency, along the lines of Levelt, Schiller & Levelt (2000), is investigated. The study reviews empirical findings on syllable structure acquisition in Dutch, German, French and English, and presents novel findings on Polish. These comparisons reveal that, to the extent allowed by implicational markedness universals, frequency covaries with acquisition order across languages. From the computational perspective, the paper shows that interacting roles of markedness and frequency in a class of constraint-based phonological learning models embody this hypothesis, and their predictions are illustrated via computational simulation.

Type
Articles
Information
Journal of Child Language , Volume 37 , Special Issue 3: Computational models of child language learning , June 2010 , pp. 565 - 606
Copyright
Copyright © Cambridge University Press 2010

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Footnotes

[*]

I would like to thank the editors, the guest editor Brian MacWhinney and an anonymous reviewer for their helpful comments, and especially Paul Boersma for his extensive review. Many thanks to Richard Weist for digitizing and sharing the audio-recordings of the Polish CHILDES data, and to Yvan Rose for providing the software and technical support to help with transcription of the data. The development of this work has also benefited by comments from Joe Pater, Karen Jesney, Kathryn Flack, Adam Albright and audiences at SUNY, NYU and the First Northeast Computational Phonology Meeting, where portions of this work were presented.

References

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