Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/777
Title: Modelling syntactic development in a cross-linguistic context
Authors: Gobet, F
Freudenthal, D
Pine, J M
Keywords: MOSAIC;innate knowledge;optional-infinitive;English;Dutch;Spanish;distributional analyser;word order errors;Universal Grammar;computational modelling
Issue Date: 2004
Publisher: Proceedings of the COLING 2004 Workshop
Citation: Gobet, F, .Freudenthal, D., & Pine, J. M. (2004). Modelling syntactic development in a cross-linguistic context. Proceedings of the COLING 2004 Workshop
Abstract: Mainstream linguistic theory has traditionally assumed that children come into the world with rich innate knowledge about language and grammar. More recently, computational work using distributional algorithms has shown that the information contained in the input is much richer than proposed by the nativist approach. However, neither of these approaches has been developed to the point of providing detailed and quantitative predictions about the developmental data. In this paper, we champion a third approach, in which computational models learn from naturalistic input and produce utterances that can be directly compared with the utterances of language-learning children. We demonstrate the feasibility of this approach by showing how MOSAIC, a simple distributional analyser, simulates the optional-infinitive phenomenon in English, Dutch, and Spanish. The model accounts for young children's tendency to use both correct finites and incorrect (optional) infinitives in finite contexts, for the generality of this phenomenon across languages, and for the sparseness of other types of errors (e.g., word order errors). It thus shows how these phenomena, which have traditionally been taken as evidence for innate knowledge of Universal Grammar, can be explained in terms of a simple distributional analysis of the language to which children are exposed.
URI: http://bura.brunel.ac.uk/handle/2438/777
Appears in Collections:Psychology
Dept of Life Sciences Research Papers

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