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Academic Paper


Title: Explaining quantitative variation in the rate of Optional Infinitive errors across languages: A comparison of MOSAIC and the Variational Learning Model
Author: Daniel Freudenthal
Institution: University of Liverpool
Author: Julian M Pine
Institution: University of Liverpool
Author: Fernand Gobet
Institution: Brunel University
Linguistic Field: Computational Linguistics; Language Acquisition
Abstract: In this study, we use corpus analysis and computational modeling techniques to compare two recent accounts of the OI stage: Legate & Yang's () Variational Learning Model and Freudenthal, Pine & Gobet's () 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.

CUP at LINGUIST

This article appears in Journal of Child Language Vol. 37, Issue 3, which you can read on Cambridge's site or on LINGUIST .



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