Speech recognition system using Markov models having independent

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

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G10L 708

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050312170

ABSTRACT:
A speech recognition system measures the values of at least two classes of features of an utterance: (1) a first class whose value is related to the frequency spectrum of the utterance, and (2) a second class whose value is related to the variation with time of the "first class" value of the utterance. Word baseforms are constructed from Markov model baseform units. Each output-producing transition of a baseform unit produces outputs from both classes. However, for each output-producing transition, the probabilities of producing outputs from the first class are independent of the probabilities of producing outputs from the second class.

REFERENCES:
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patent: 4829577 (1989-05-01), Kuroda et al.
Bahl, L. R., et al "Acoustic Markov Models used in the Tangora Speech Recognition System", Proceedings of ICASSP '88, Apr. 1988, S11-3.
Bahl, L. R. et al "A Maximum Likelihood Approach to Continuous Speech Recognition", IEEE Trans. Pattern Analysis and Machine Intelligence, vol. PAMI-5, No. 2, pp. 179-190, 1983.
Jelinek, F. "Continuous Speech Recognition By Statistical Methods", Proc. IEEE, vol. 64, 1976, pp. 532-556.
Levinson, S. E., et al "An Introduction to the Application of the Theory of Probabilistic Functions of the Markov Process of Automatic Speech Recognition", The Bell System Technical Journal, vol. 64, No. 4, pp. 1035-1074, Apr. 1983.

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