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Title: US5502791: Speech recognition by concatenating fenonic allophone hidden Markov models in parallel among subwords
[ Derwent Title ]


Country: US United States of America

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13 pages

 
Inventor: Nishimura, Masafumi; Yokohama, Japan
Okochi, Masaaki; Yokohama, Japan

Assignee: International Business Machines Corporation, Armonk, NY
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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Published / Filed: 1996-03-26 / 1993-09-01

Application Number: US1993000114709

IPC Code: Advanced: G10L 15/06; G10L 15/14; G10L 15/18; G10L 15/02;
IPC-7: G10L 9/00;

ECLA Code: G10L15/14M; G10L15/187; S10L15/063C; S10L15/197;

U.S. Class: Current: 704/256; 704/E15.02; 704/E15.032;
Original: 395/002.65;

Field of Search: 395/002,2.64-2.66,2.6-2.63 381/041,42,43,45

Priority Number:
1992-09-29  JP1992000259301

Abstract:     Analysis of a word input from a speech input device 1 for its features is made by a feature extractor 4 to obtain a feature vector sequence corresponding to said word, or to obtain a label sequence by applying a further transformation in a labeler 8. Fenonic hidden Markov models for speech transformation candidates are combined with N-gram probabilities (where N is all integer greater than or equal to 2) to produce models of words. The recognizer determines the probability that the speech model composed for each candidate word would output the label sequence or feature vector sequence input as speech, and outputs the candidate word corresponding to the speech model having the highest probability to a display 19.

Attorney, Agent or Firm: Schechter, Marc D. ; Tassinari, Jr., Robert P. ;

Primary / Asst. Examiners: MacDonald, Allen R.; Sartori, Michael A.

Maintenance Status: E3 Expired  Check current status

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Designated Country: DE FR GB 

Family: Show 8 known family members

First Claim:
Show all 6 claims
We claim:     1. A speech recognizer comprising:
  • means for analyzing a word inputted as speech for its features and thus obtaining a label sequence or feature vector sequence corresponding to said word;
  • means for retaining hidden Markov models respectively for one or more allophones of subwords of each speech transformation candidate;
  • dictionary means for retaining a plurality of candidate words to be recognized;
  • means for composing a speech model by concatenating each hidden Markov model for allophones of each speech transformation candidate in parallel among subwords in correspondence to a candidate word;
  • means for determining a probability of a speech model composed with regard to each candidate word to output the label sequence or feature vector sequence of said word inputted as speech, and outputting the candidate word corresponding to a speech model of a highest probability as a result of recognition.


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Forward References: Show 48 U.S. patent(s) that reference this one

       
U.S. References: Go to Result Set: All U.S. references   |  Forward references (48)   |   Backward references (6)   |   Citation Link

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PDF
Patent  Pub.Date  Inventor Assignee   Title
Get PDF - 30pp US4817156  1989-03 Bahl et al.  International Business Machines Corporation Rapidly training a speech recognizer to a subsequent speaker given training data of a reference speaker
Get PDF - 13pp US5031217  1991-07 Nishimura  International Business Machines Corporation Speech recognition system using Markov models having independent label output sets
Get PDF - 16pp US5129001  1992-07 Bahl et al.  International Business Machines Corporation Method and apparatus for modeling words with multi-arc markov models
Get PDF - 16pp US5199077  1993-03 Wilcox et al.  Xerox Corporation Wordspotting for voice editing and indexing
Get PDF - 13pp US5278942  1994-01 Bahl et al.  International Business Machines Corporation Speech coding apparatus having speaker dependent prototypes generated from nonuser reference data
Get PDF - 14pp US5317673  1994-05 Cohen et al.  SRI International Method and apparatus for context-dependent estimation of multiple probability distributions of phonetic classes with multilayer perceptrons in a speech recognition system
       
Foreign References:
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Publication Date IPC Code Assignee   Title
Get PDF - 10pp EP0362785A2 1990-04  G10L 5/06 NEC CORP Continuous speech recognition unit 
Get PDF - 12pp EP0504927A2 1992-09  G10L 5/06 Kabushiki Kaisha Toshiba Speech recognition system and method 
Buy PDF- 34pp GB2240203 1991-07  G10L 5/06 * APPLE COMPUTER, INC. AUTOMATED SPEECH RECOGNITION SYSTEM 


Other Abstract Info: DERABS G1994-111319 JAPABS 180391P000036

Other References:
  • L. R. Bahl et al., "Acoustic Markov Models Used in the Tangora Speech Recognition System," ICASSP '88, Apr. 11-14, 1988, pp. 497-500.
  • Bahl, L. R., et al. "Acoustic Markov Models Used In The Tangora Speech Recognition System." Proceedings of the 1988 IEEE International Conference on Acoustics, Speech, and Signal Processing, S11-13, pp. 497-500, Apr. 1988.
  • Bahl, L. R., et al. "A Maximum Likelihood Approach to Continuous Speech Recognition." IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. PAMI-5, No. 2, pp. 179-190, Mar. 1983. (12 pages) Cited by 42 patents
  • Schwartz, R., et al. "Context-Dependent Modeling For Acoustic-Phonetic Recognition Of Continuous Speech." Proceedings of the 1985 IEEE International Conference on Acoustics, Speech, and Signal Processing, Tampa, Florida, pp. 1205-1208, Mar. 1985.


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