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Explaining quantitative variation in the rate of Optional Infinitive errors across languages: A comparison of MOSAIC and the Variational Learning Model*

Published online by Cambridge University Press:  25 March 2010

DANIEL FREUDENTHAL ,
JULIAN PINE  and
FERNAND GOBET
DANIEL FREUDENTHAL*
Affiliation:
University of Liverpool
JULIAN PINE
Affiliation:
University of Liverpool
FERNAND GOBET
Affiliation:
Brunel University
*
Address for correspondence:Daniel Freudenthal, School of Psychology, University of Liverpool, Bedford Street South Liverpool, L69 7ZA, United Kingdom. tel: 0151 794 1108; e-mail: D.Freudenthal@liverpool.ac.uk
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Abstract

In this study, we use corpus analysis and computational modelling techniques to compare two recent accounts of the OI stage: Legate & Yang's (2007) Variational Learning Model and Freudenthal, Pine & Gobet's (2006) Model of Syntax Acquisition in Children. We first assess the extent to which each of these accounts can explain the level of OI errors across five different languages (English, Dutch, German, French and Spanish). We then differentiate between the two accounts by testing their predictions about the relation between children's OI errors and the distribution of infinitival verb forms in the input language. We conclude that, although both accounts fit the cross-linguistic patterning of OI errors reasonably well, only MOSAIC is able to explain why verbs that occur more frequently as infinitives than as finite verb forms in the input also occur more frequently as OI errors than as correct finite verb forms in the children's output.

Information

Type
Articles
Information
Journal of Child Language , Volume 37 , Special Issue 3: Computational models of child language learning , June 2010 , pp. 643 - 669
Copyright
Copyright © Cambridge University Press 2010

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Footnotes

[*]

We would like to thank the Max Planck Institute for Evolutionary Anthropology, Leipzig for allowing us access to the Leo Corpus. This research was funded by the ESRC under Grant Number RES-062-23-1348.

References

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