Algebraic learning for language acquisition

Kevin R. Farrell; Richard J. Mammone; Allen Gorin

doi:10.1117/12.172523

1 February 1994 Algebraic learning for language acquisition

Kevin R. Farrell, Richard J. Mammone, Allen Gorin

Proceedings Volume 2093, Substance Identification Analytics; (1994) https://doi.org/10.1117/12.172523
Event: Substance Identification Technologies, 1993, Innsbruck, Austria

Abstract

This paper explores the application of new algorithms to the adaptive language acquisition model formulated by Gorin. The new methods consists of incremental approaches for the algebraic learning of statistical associations proposed by Tishby. The incremental methods are evaluated on a text-based natural language experiment, namely the inward call manager task. Performance is evaluated with respect to the alternative methods, namely the smooth mutual information method and the pseudo-inverse solution.

Citation Download Citation

Kevin R. Farrell, Richard J. Mammone, and Allen Gorin "Algebraic learning for language acquisition", Proc. SPIE 2093, Substance Identification Analytics, (1 February 1994); https://doi.org/10.1117/12.172523

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