Speech recognition method and system

Details Speech recognition method and system Speech recognition method and system

2008-01-15

2008-01-15

Hudspeth, David (Department: 2626)

Data processing: speech signal processing, linguistics, language

Speech signal processing

Recognition

C704S251000, C704S253000, C704S254000, C704S255000, C704S256000, C704S256100, C704S232000

Reexamination Certificate

active

10020895

ABSTRACT:
A speech recognition system uses a phoneme counter to determine the length of a word to be recognized. The result is used to split a lexicon into one or more sub-lexicons containing only words which have the same or similar length to that of the word to be recognized, so restricting the search space significantly. In another aspect, a phoneme counter is used to estimate the number of phonemes in a word so that a transition bias can be calculated. This bias is applied to the transition probabilities between phoneme models in an HNN based recognizer to improve recognition performance for relatively short or long words.

REFERENCES:
patent: 5003601 (1991-03-01), Watari et al.
patent: 5218668 (1993-06-01), Higgins et al.
patent: 5390278 (1995-02-01), Gupta et al.
patent: 5617509 (1997-04-01), Kushner et al.
patent: 5621859 (1997-04-01), Schwartz et al.
patent: 5638487 (1997-06-01), Chigier
patent: 5687287 (1997-11-01), Gandhi et al.
patent: 5737716 (1998-04-01), Bergstrom et al.
patent: 5745649 (1998-04-01), Lubensky
patent: 6073095 (2000-06-01), Dharanipragada et al.
patent: 6138095 (2000-10-01), Gupta et al.
patent: 6505153 (2003-01-01), Van Thong et al.
patent: 6539353 (2003-03-01), Jiang et al.
patent: 6801891 (2004-10-01), Garner et al.
patent: 2001/0056346 (2001-12-01), Ueyama et al.
D.A. James and S.J. Young. “A Fast Lattice-Based Approach to Vocabulary Independent Wordspotting”, ICASSP 1994, pp. 377-380.
L. R. Bahl, P. F. Brown, P. V. de Souza and R. L. Mercer, “Speech Recognition with Hidden Markov Models of Speech Waveforms,” IBM Technical Disclosure Bulletin, vol. 34, No. 1, Jun. 1991, pp. 7-16.
Koumpis, K. et al: “Adaptive Transition Bias for Robust Low Complexity Speech Recognition”, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing Proceedings (Cat. No. 01CH37221), May 7-11, 2001, pp. 277-280, vol. 1, XP002232855, Salt Lake City, UT, USA, Piscataway, NJ, ISBN: 0-7803-7041-4.
Gerber, Christoph: “A general Approach to Speech Recognition”, Proceedings of the Final Workshop on Multimedia Information Retrieval (MIRO '95), Sep. 18-20, 1995, XP002232856, Glasgow, Scotland, pp. 1-12.
Krogh, Anders et al : “Hidden Neural Networks”, Neural Computation, Feb. 15, 1999, MIT Press, USA, vol. 11. No. 2, pp. 541-563, XP002232857, ISSN: 0899-7667.
Russell, M. J., et al: “Measure of Local Speaking-Rate for Automatic Speech Recognition”, Electronics Letters, IEE Stevenage, GB, vol. 35, No. 10, May 13, 1999, pp. 787-789, XP 006012165, ISSN: 0013-5194.
European Search Report.
Lawrence R. Rabiner; A Tutorial on Hidden Markov Models and Selected Applications in Speech Recognition; Proceedings of the IEEE; Feb. 2, 1989; vol. 77; Issue 22.
Soren Kamaric Riis; Hidden Markov Models and Neural Networks for Speech Recognition; Ph.D. Technical University of Denmark, Department of Mathematical Modelling; Thesis; Apr. 20, 1998; Lyngby, Denmark.
Soren Kamaric Riis & Olli Viikki; Low Complexity Speaker Independent Command Word Recognition in Car Environments.
Youngjoo Suh & Younjik Lee; Phoneme Segmentation of Continuous Speech Using Multi-Layer Perceptron.

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