The logical problem of language acquisition : a probabilistic perspective
Hsu, Anne S. and Chater, Nick. (2010) The logical problem of language acquisition : a probabilistic perspective. Cognitive Science, Vol.34 (No.6). pp. 972-1016. ISSN 0364-0213Full text not available from this repository.
Official URL: http://dx.doi.org/10.1111/j.1551-6709.2010.01117.x
Natural language is full of patterns that appear to fit with general linguistic rules but are ungrammatical. There has been much debate over how children acquire these “linguistic restrictions,” and whether innate language knowledge is needed. Recently, it has been shown that restrictions in language can be learned asymptotically via probabilistic inference using the minimum description length (MDL) principle. Here, we extend the MDL approach to give a simple and practical methodology for estimating how much linguistic data are required to learn a particular linguistic restriction. Our method provides a new research tool, allowing arguments about natural language learnability to be made explicit and quantified for the first time. We apply this method to a range of classic puzzles in language acquisition. We find some linguistic rules appear easily statistically learnable from language experience only, whereas others appear to require additional learning mechanisms (e.g., additional cues or innate constraints).
|Item Type:||Journal Article|
|Subjects:||H Social Sciences > H Social Sciences (General)|
|Divisions:||Faculty of Social Sciences > Warwick Business School > Behavioural Science
Faculty of Social Sciences > Warwick Business School
|Journal or Publication Title:||Cognitive Science|
|Official Date:||August 2010|
|Number of Pages:||45|
|Page Range:||pp. 972-1016|
|Access rights to Published version:||Restricted or Subscription Access|
Actions (login required)