Adaptive language acquisition using incremental learning

Authors:
K. Farrell;R. J. Mammone;A. L. Gorin
Affiliations:
CAIP Center, Rutgers University, Piscataway, New Jersey;CAIP Center, Rutgers University, Piscataway, New Jersey;AT&T Bell Laboratories, Murray Hill, New Jersey
Venue:
ICASSP'93 Proceedings of the 1993 IEEE international conference on Acoustics, speech, and signal processing: plenary, special, audio, underwater acoustics, VLSI, neural networks - Volume I
Year:
1993

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Abstract

An incremental approach to solving an algebraic formulation of the language acquisition problem is presented. This problem consists of solving a system of linear equations, where each equation represents a sentence/action pair and each variable denotes a word/action association [1]. The algebraic model for language acquisition has been shown [1] to provide advantages over the relative frequency estimate models when dealing with small-sample statistics. In this paper, two incremental methods are investigated to solve the system of linear equations. The incremental methods provide a regularized solution that is shown experimentally to be advantageous over the pseudoinverse solution for classifying test data. In addition, the methods are more efficient with respect to computational and memory requirements.