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Title: US4882759: Synthesizing word baseforms used in speech recognition
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Country: US United States of America

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23 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: 1989-11-21 / 1986-04-18

Application Number: US1986000853525

IPC Code: Advanced: G10L 11/00; G10L 15/06; G10L 15/14;
IPC-7: G10L 5/00;

ECLA Code: G10L15/14; T05K999/99;

U.S. Class: Current: 704/243; 704/255;
Original: 381/051; 381/043; 381/036;

Field of Search: 381/036-43,51-53 364/513.5

Priority Number:
1986-04-18  US1986000853525

Abstract:     Apparatus and method for synthesizing word baseforms for words not spoken during a training session, wherein each synthesized baseform represents a series of models from a first set of models, which include: (a) uttering speech during a training session and representing the uttered speech as a sequence of models from a second set of models; (b) for each of at least some of the second set models spoken in a given phonetic model context during the training session, storing a respective string of first set models; and (c) constructing a word baseform of first set models for a word not spoken during the training session, including the step of representing each piece of a word that corresponds to a second set model in a given context by the stored respective string, if any, corresponding thereto.

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

Primary / Asst. Examiners: Kemeny, Emanuel S.;

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Designated Country: DE FR GB IT 

Family: Show 9 known family members

First Claim:
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We claim:     1. A method of synthesizing word baseforms for words wherein each synthesized baseform represents a series of models from a first set of models, each model of the first set corresponding to an output-related model wherein each output-related model correlates to an output generable by an acoustic processor, the method comprising the steps of:
  • (a) forming words as respective sequences of models from a second set of models, each model of the second set corresponding to a phonetic model;
  • (b) for a second set model occurring in a given context of second set models in step (a), storing a respective string of first set models;
  • (c) performing step (b) for each of at least one second set model; and
  • (d) constructing a word baseform of first set models for a word formed in step (a), including the step of representing each piece of a word that corresponds to a second set model in a given context by the stored respective string of first set models, if any, corresponding thereto.


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Forward References: Show 32 U.S. patent(s) that reference this one

       
U.S. References: Go to Result Set: All U.S. references   |  Forward references (32)   |   Backward references (4)   |   Citation Link

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Patent  Pub.Date  Inventor Assignee   Title
Get PDF - 44pp US4181821  1980-01 Pirz et al.  Bell Telephone Laboratories, Incorporated Multiple template speech recognition system
Get PDF - 9pp US4513436  1985-04 Nose et al.  Oki Electric Industry, Co., Ltd. Speech recognition system
Get PDF - 20pp US4587670  1986-05 Levinson et al.  AT&T Bell Laboratories Hidden Markov model speech recognition arrangement
Get PDF - 28pp US4593367  1986-06 Slack et al.  ITT Corporation Probabilistic learning element
       
Foreign References:
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Publication Date IPC Code Assignee   Title
Buy PDF GB0025685 1981-03    PLIVA D.D. MACROLIDES 
  GB0033412 1981-12       


Other Abstract Info: DERABS G87-293215

Other References:
  • ICASSP 84 Proceedings of the IEEE International Conf on ASSP, Mar. 1984, vol. 3, pp. 35.6.1-35.6.4 "Improved Hidden Markov Modeling of Phonemes for Continuous Speech Recognition" by R. Schwartz.
  • ICASSP 84 Proceedings of the IEEE International Conf on ASSP, Mar. 1984 pp. 42.5.1-42.5.4 "An Information Theoretic Approach to the Automatic Determination of Phonemic Baseforms" by J. M. Lucassen.
  • IEEE Trans on Acoustics, Speech and Signal Processing, vol. ASSP-28, No. 2, Apr. 1980, pp. 129-136, "A Training Procedure for Isolated Word Recognition Systems" by S. Furui. (8 pages) Cited by 3 patents
  • Research Disclosure, nr. 256, Aug. 1985, p. 418, Abstract No. 25649, Emsworth, Hampshire, GB; "Composite Fenemic Phones".
  • IBM Technical Disclosure Bulletin, vol. 24, No. 4, Sep. 1981, pp. 2042-2043, New York; L. R. Bahl et al "Automatic Selection of Speech Prototypes".
  • M. Cravero et al, "Phonetic Units for Hidden Markov Models", CSELT Technical Report, vol. 14, No. 2, Oct. 7, 1986, pp. 121-125.
  • B. H. Juang et al, "Recent Developments in the Application of Hidden Markov Models to Speaker-Independent Isolated Word Recognition", IEEE, 1985, pp. 1.3.1-1.3.4.
  • H. Bourlard et al, "Speaker Dependent Connected Speech Recognition via Phonemic Markov Models", IEEE, 1985, pp. 1213-1216.
  • Y. Kamp et al, "State Reduction in Hidden Markov Chains Used for Speech Recognition", IEEE, 1985, pp. 1138-1145. (8 pages) Cited by 3 patents
  • R. Schwartz et al, "Context-Dependent Modeling for Acoustic-Phonetic Recognition of Continuous Speech", IEEE 1985, pp. 1205-1208.
  • J. P. Mari et al, "Speaker Independent Connected Digit Recognition Using Hidden Markov Models", Speech Tech '85, vol. 1, No. 2, pp. 127-132.
  • S. Levinson et al, "Speaker Independent Isolated Digit Recognition Using Hidden Markov Models", IEEE, 1983, pp. 1049-1052.
  • D. M. Choy et al, "Speech Compression by Phoneme Recognition", IBM TDB, vol. 25, No. 6, Nov. 1982, pp. 2884-2886.
  • R. Bakis et al, "Continuous Speech Recognition via Centisecond Acoustic States", Research Report, 1978, pp. 1-9.
  • R. Bakis, "Spoken Word Spotting via Centisecond Acoustic States", IBM TDB vol. 18, No. 10, Mar. 1976, pp. 3479-3481.


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