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Abstract

Francisco J. Nevado, Joan-Andreu Sánchez, José-Miguel Benedí. Lexical Decoding Based on the Combination of Category-Based Stochastic Models and Word-Category Distribution Models. IX Spanish Symposium on Pattern Recognition and Image Analysis, 2001. pp. 183-188. Publicacions de la Universitat Jaume I.

Lexical decoding is the obtaining of the most probable sequence of categories associated to a sequence of words. This paper describes two lexical decoding combined models which are based on a stochastic category-based model and a probabilistic model of word distribution into linguistic categories. In the first combined model, the stochastic category-based model is a Stochastic Context-Free Grammar, and in the second combined model, the stochastic category-based model is a n-gram model. The estimation processes of the models are described in detail. Finally, experiments on the Wall Street Journal corpus are reported.