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The Lexical Access Problem consists of determining the intended sequence ofwords corresponding to an input sequence of phonemes (basic speech sounds) thatcome from a low-level phoneme recognizer. In this paper we present aninformation-theoretic approach based on the Minimum Message Length Criterionfor solving the Lexical Access Problem. We model sentences using phonemerealizations seen in training, and word and part-of-speech information obtainedfrom text corpora. We show results on multiple-speaker, continuous, read speechand discuss a heuristic using equivalence classes of similar sounding wordswhich speeds up the recognition process without significant deterioration inrecognition accuracy.

Lexical Access for Speech Understanding using Minimum Message Length Encoding