Speech recognition method

Electrical audio signal processing systems and devices – One-way audio signal program distribution – Public address system

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381 43, G10L 100, G10L 500

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048295779

ABSTRACT:
Speaker adaptation which enables a person to use a Hidden Markov model type recognizer previously trained by another person or persons. During initial training, parameters of Markov models are calculated iteratively by, for example, using the Forward-Backward algorithm. Adapting the recognizer to a new speaker involves (a) storing and utilizing intermediate results or probabilistic frequencies of a last iteration of training parameters, and (b) calculating new parameters by computing a weighted sum of the probabilistic frequencies stored during training and frequencies obtained from adaptation data derived from known utterances of words made by the new speaker.

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patent: 4718094 (1988-01-01), Bahl et al.
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patent: 4783803 (1988-11-01), Baker et al.
"A Maximum Likelihood Approach to Continuous Speech Recognition" (IEEE Transactions on Pattern Analysis and Machine Intelligence, PAMI-vol. 5, No. 2, pp. 179-190, 1983, Lalit R. Bahl, Frederick Jelinek and Robert L. Mercer).
"Continuous Speech Recognition by Statistical Methods" (Proceedings of the IEEE-vol. 64, 1976, pp. 532-556, Frederick Jelinek).
"An Introduction to the Application of the Theory of Probabilistic Functions of a Markov Process to Automatic Speech Recognition" (The Bell System Technical Journal-vol. 62, No. 4, 1983, pp. 1035-1074, Apr., S. E. Levinson, L. R. Rabiner and M. M. Sondhi.

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