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Title: US5165007: Feneme-based Markov models for words
[ Derwent Title ]


Country: US United States of America

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9 pages

 
Inventor: Bahl, Lalit R.; Amawalk, NY
DeSouza, Peter V.; Yorktown Heights, NY
Mercer, Robert L.; Yorktown Heights, NY
Picheny, Michael A.; White Plains, NY

Assignee: International Business Machines Corporation, Armonk, NY
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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Published / Filed: 1992-11-17 / 1989-06-12

Application Number: US1989000366231

IPC Code: Advanced: G10L 15/14; G10L 15/02; G10L 15/06;
IPC-7: G10L 5/06;

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

U.S. Class: Current: 704/243; 704/256; 704/E15.028;
Original: 395/002; 381/043;

Field of Search: 381/041-50 395/002

Priority Number:
1989-06-12  US1989000366231
1985-02-01  US1985000697174

Abstract:     In a speech recognition system, apparatus and method for modelling words with label-based Markov models is disclosed. The modelling includes: entering a first speech input, corresponding to words in a vocabulary, into an acoustic processor which converts each spoken word into a sequence of standard labels, where each standard label corresponds to a sound type assignable to an interval of time; representing each standard label as a probabilistic model which has a plurality of states, at least one transition from a state to a state, and at least one settable output probability at some transitions; entering selected acoustic inputs into an acoustic processor which converts the selected acoustic inputs into personalized labels, each personalized label corresponding to a sound type assigned to an interval of time; and setting each output probability as the probability of the standard label represented by a given model producing a particular personalized label at a given transition in the given model. The present invention addresses the problem of generating models of words simply and automatically in a speech recognition system.

Attorney, Agent or Firm: Schechter, Marc D. ;

Primary / Asst. Examiners: Fleming, Michael R.; Knepper, David D.

Maintenance Status: E3 Expired  Check current status

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Related Applications:
Application Number Filed Patent Pub. Date  Title
US1985000697174 1985-02-01       


       
Parent Case:     This is a continuation of application Ser. No. 697,174, filed Feb. 1, 1985.

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First Claim:
Show all 2 claims
We claim:     1. An apparatus for modeling words, said apparatus comprising:
  • means for measuring the value of at least one feature of an utterance of a first word, said utterance occurring over a series of successive time intervals of equal duration Δt, said means measuring the feature value of the utterance during each time interval to produce a series of feature vector signals representing the feature values;
  • means for storing a finite set of probabilistic model signals, each probabilistic model signal representing a probabilistic model of a component sound, each probabilistic model comprising a Markov model having (a) only first and second states, (b) a first transition extending from the first state to the second state, (c) a second transition extending from the first state back to itself, (d) a null transition extending from the first state to the second state, (e) a transition probability for each transition, (f) an output probability for each output signal belonging to a finite set of output signals that the output signal will be produced at the first transition, (g) an output probability for each output signal that the output signal will be produced at the second transition, and (h) an output probability of zero for each output signal that the output signal will be produced at the null transition, each output signal of each Markov model representing the value of at least one feature of an utterance measured over a time interval having a duration substantially equal to Δt;
  • means for storing a finite set of training label vector signals, each training label vector signal having an associated probabilistic model signal, each training label vector signal having at least one parameter value;
  • means for comparing the feature value, of each feature vector signal in the series of feature vector signals produced by the measuring means as a result of the utterance of the first word, to the parameter values of the training label vector signals to determine, for each feature vector signal, the closest associated training label vector signal;
  • means for forming a baseform of the first word from the series of feature vector signals by substituting, for each feature vector signal, the closest associated training label vector signal to produce a baseform series of training label vector signals; and
  • means for forming a probabilistic model of the first word from the baseform series of training label vector signals by substituting, for each training label vector signal, the associated probabilistic model signal to produce a series of probabilistic model signals.


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Forward References: Show 23 U.S. patent(s) that reference this one

       
U.S. References: Go to Result Set: All U.S. references   |  Forward references (23)   |   Backward references (7)   |   Citation Link

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Patent  Pub.Date  Inventor Assignee   Title
Get PDF - 15pp US4032710  1977-06 Martin et al.  Threshold Technology, Inc. Word boundary detector for speech recognition equipment
Get PDF - 27pp US4156868  1979-05 Levinson et al.  Bell Telephone Laboratories, Incorporated Syntactic word recognizer
Get PDF - 44pp US4181821  1980-01 Pirz et al.  Bell Telephone Laboratories, Incorporated Multiple template speech recognition system
Get PDF - 47pp US4319085  1982-03 Welch et al.  Threshold Technology Inc. Speech recognition apparatus and method
Get PDF - 21pp US4383135  1983-05 Scott et al.  Scott Instruments Corporation Method and apparatus for speech recognition
Get PDF - 25pp US4555796  1985-11 Sakoe  Nippon Electric Co., Ltd. DP Matching system for recognizing a string of words connected according to a regular grammar
Get PDF - 20pp US4587670  1986-05 Levinson et al.  AT&T Bell Laboratories Hidden Markov model speech recognition arrangement
       
Foreign References: None

Other Abstract Info: DERABS G88-155394

Other References:
  • Bahl et al., "A Maximum Likelihood Approach to Continuous Speech Recognition", IEEE Trans on Pattern Analysis and Machine Intelligence, vol. PAMI-5, No. 2, Mar. 1983, pp. 179-190. (12 pages) Cited by 42 patents
  • IEEE Trans on acoustics, speech & signal processing, vol. ASSP-28, No. 2, Apr., 1980 "A Training Procedure for Isolated Word Recognition Systems" by Sadaoki Furui--pp. 129-136. (8 pages) Cited by 3 patents
  • IEEE ASSP Magazine, Apr. 1984, pp. 4-29 "Vector Quantization" by Robert M. Gray.
  • Proceedings ICASSP, 1981, pp. 1153-1155 "Continuous Speech Recognition With Automatically Selected Acoustic Prototypes Obtained by Either Bootstrapping or Clustering" by A. Nadas et al.
  • Spoken Word Spotting Via Centisecond Acoustic States, R. Bakis, , IBM Technical Disclosure Bulletin, vol. 18, No. 10, March 1976, pp. 3479-3481, New York, U.S.
  • Speacker Dependent Connected Speech Recognition Via Phonemic Markov Models, H. Bourlard et al., ICASSP '85, Tampa, Fla. U.S., 26th-29th Mar. 1985, vol. 3, pp. 1213-1216, IEEE New York, U.S.
  • IBM Research Report, #5971, Apr. 5, 1976 "Continuous Speech Recognition Via Centisecond Acoustic States" R. Bakis, pp. 1-8 and title page with abstract.
  • Proceedings of the IEEE, vol. 64, No. 4, Apr. 1976 "Continuous Speech Recognition by Statistical Methods" F. Jelinek pp. 532-556. (25 pages) Cited by 30 patents
  • Reprinted from IEEE Trans. Acoust., Speech, and Signal Process., vol. ASSP-23, pp. 67-72, Feb. 1975, "Minimum Prediction Residual Principle Applied to Speech Recognition", by Fumitada Itakura. (6 pages) Cited by 22 patents


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