The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar
The Informational Complexity of Learning: Perspectives on Neural Networks and Generative Grammar
Ambiguity and the computational feasibility of syntax acquisition
Ambiguity and the computational feasibility of syntax acquisition
Psychocomputational linguistics: a gateway to the computational linguistics curriculum
TeachCL '08 Proceedings of the Third Workshop on Issues in Teaching Computational Linguistics
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An investment of effort over the last two years has begun to produce a wealth of data concerning computational psycholinguistic models of syntax acquisition. The data is generated by running simulations on a recently completed database of word order patterns from over 3,000 abstract languages. This article presents the design of the database which contains sentence patterns, grammars and derivations that can be used to test acquisition models from widely divergent paradigms. The domain is generated from grammars that are linguistically motivated by current syntactic theory and the sentence patterns have been validated as psychologically/developmentally plausible by checking their frequency of occurrence in corpora of child-directed speech. A small case-study simulation is also presented.