A Markov language learning model for finite parameter spaces

Authors:
Partha Niyogi;Robert C. Berwick
Affiliations:
Massachusetts Institute of Technology, Cambridge, MA;Massachusetts Institute of Technology, Cambridge, MA
Venue:
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Year:
1994

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Abstract

This paper shows how to formally characterize language learning in a finite parameter space as a Markov structure. Important new language learning results follow directly: explicitly calculated sample complexity learning times under different input distribution assumptions (inclding CHILDES database language input) and learning regimes. We also briefly describe a new way to formally model (rapid) diachronic syntax change.