Abstract
A computational framework is presented which is used to model the process by which human language learners acquire the syntactic component of their native language. The focus is feasibility - is acquisition possible within a reasonable amount of time and/or with a reasonable amount of work? The approach abstracts away from specific linguistic descriptions in order to make a 'broad-stroke' prediction of an acquisition model's behavior by formalizing factors that contribute to cross-linguistic ambiguity. Discussion centers around an application to Fodor's Structural Trigger's Learner (STL) (1998)1and concludes with the proposal that successful computational modeling requires a parallel psycholinguistic investigation of the distribution of ambiguity across the domain of human languages.
Cite
CITATION STYLE
Sakas, W. G. (2000). Modeling the effect of cross-language ambiguity on human syntax acquisition. In Proceedings of the 4th Conference on Computational Natural Language Learning, CoNLL 2000 and of the 2nd Learning Language in Logic Workshop, LLL 2000 - Held in cooperation with ICGI 2000 (pp. 61–66). Association for Computational Linguistics (ACL). https://doi.org/10.3115/1117601.1117614
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