The MIT SUMMIT Speech Recognition system: a progress report
HLT '89 Proceedings of the workshop on Speech and Natural Language
Some applications of tree-based modelling to speech and language
HLT '89 Proceedings of the workshop on Speech and Natural Language
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A probabilistic approach to lexical access from a recognized phone sequence is presented. Lexical access is seen as finding the word sequence that maximizes the lexical likelihood of a sequence of phones and durations as recognized by a phone recognizer. This is theoretically correct for minimum error rate recognition within the model presented and is intuitively pleasing since it means that the "confusion matrix" of the phone recognizer will be learned and its regularities exploited. The lexical likelihoods are estimated from training data provided by the phone recognizer using statistical decision trees. Classification trees are used to estimate the phone realiziation distributions and regression trees are used to estimate the phone duration distributions. We find they can capture effectively allophonic variation, alternative pronunciation, word co-articulation and segmental durations. We describe a simpified, but efficient implementation of these models to lexical access in the DARPA resource management recognitiion task.