Speech recognizer

Details Speech recognizer Speech recognizer

1995-06-07

1998-04-07

Zele, Krista

395 264, G10L 506

Patent

active

057374880

ABSTRACT:
In order to recognize input speech by analyzing the input speech at a predetermined time interval, extracting feature vectors and calculating likelihood value of a reference pattern model of each category to be recognized. A first probability calculation means calculates a probability that a first hidden Markov model having internal state number as output symbol for each of categories to be recognized outputs an internal state number. A second probability calculation means calculates a probability that a second hidden Markov model having transition probabilities of internal state number and feature vector output probability distribution for each of the respective internal state numbers outputs a feature vector. A likelihood value calculation means calculates likelihood value of a reference pattern model of the category to be recognized by using outputs of the first and second probability calculation means.

REFERENCES:
patent: 5199077 (1993-03-01), Wilcox et al.
patent: 5241619 (1993-08-01), Schwartz et al.
patent: 5268990 (1993-12-01), Cohen et al.
Sukkar et al., "A Two Pass Classifier for Utterance Rejection in Keyword Spotting", ICASSP-93, vol. 2, pp. 451-454, Apr. 27-30, 1993.
Su et al., "Speech Recognition Using Weighted HMM and Subspace Projection Approaches", IEEE Transactions on Speech and Audio Processing vol. 2, No. 1, Part 1, pp. 69-79, Jan. 1994.
X.D. Huang et al., "Semi-Continuous Hidden Markov Models For Speech Signals", Computer and Language (1989) 3, pp. 239-251.
Y. Ariki, "Two-Stage Transition Mixture Distribution HMM", Proceeding I of the Society of Acoustical Engineers of Japan, Oct., 1992, pp. 85-86.
S. Takahashi et al., "Evaluation Of Semi-Continuous Bigram Restricted HMM With Continuous Speech", Proceeding I of the Society of Acoustical Engineers of Japan, Oct., 1992, pp. 159-160.

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