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Title: US5033087: Method and apparatus for the automatic determination of phonological rules as for a continuous speech recognition system
[ Derwent Title ]

Country: US United States of America

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31 pages

Inventor: Bahl, Lalit R.; Amawal, NY
Brown, Peter F.; New York, NY
DeSouza, Peter V.; Yorktown Heights, NY
Mercer, Robert L.; Yorktown Heights, NY

Assignee: International Business Machines Corp., Armonk, NY
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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Published / Filed: 1991-07-16 / 1989-03-14

Application Number: US1989000323479

IPC Code: Advanced: G10L 11/00; G10L 15/06; G10L 15/14;
IPC-7: G01L 7/08;

ECLA Code: G10L15/14; T05K999/99;

U.S. Class: Current: 704/256.5; 704/245;
Original: 381/043;

Field of Search: 381/041-46 364/513.5

Priority Number:
1989-03-14  US1989000323479

Abstract:     A continuous speech recognition system includes an automatic phonological rules generator which determines variations in the pronunciation of phonemes based on the context in which they occur. This phonological rules generator associates sequences of labels derived from vocalizations of a training text with respective phonemes inferred from the training text. These sequences are then annotated with their phoneme context from the training text and clustered into groups representing similar pronunciations of each phoneme. A decision tree is generated using the context information of the sequences to predict the clusters to which the sequences belong. The training data is processed by the decision tree to divide the sequences into leaf-groups representing similar pronunciations of each phoneme. The sequences in each leaf-group are clustered into sub-groups representing respectively different pronunciations of their corresponding phoneme in a give context. A Markov model is generated for each sub-group. The various Markov models of a leaf-group are combined into a single compound model by assigning common initial and final states to each model. The compound Markov models are used by a speech recognition system to analyze an unknown sequence of labels given its context.

Attorney, Agent or Firm: Ratner & Prestia ;

Primary / Asst. Examiners: Harkcom, Gary V.; Merecki, John A.

Maintenance Status: E3 Expired  Check current status

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Designated Country: DE FR GB IT 

Family: Show 9 known family members

First Claim:
Show all 24 claims
The invention claimed is:     1. A method for automatically separating vocalizations of language components into a plurality of groups representing pronunciations of the language components in respectively different contexts, said method comprising the steps of:
  • A) processing a training text and vocalizations representing the training text to obtain a plurality of samples representing the language components of said vocalizations;
  • B) selecting, from among the plurality of samples, a set of samples representing respective instances of a selected language component in the vocalizations;
  • C) annotating each of said selected samples with a context indicator, representing at least one language component in a contextual relationship with the selected sample, to produce annotated samples;
  • D) separating the selected samples into respectively different leaf groups based on the respective context indicators of said annotated samples, each of said leaf groups representing a pronunciation of said selected language component in a respectively different context.

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Forward References: Show 90 U.S. patent(s) that reference this one

U.S. References: Go to Result Set: All U.S. references   |  Forward references (90)   |   Backward references (11)   |   Citation Link

Patent  Pub.Date  Inventor Assignee   Title
Get PDF - 9pp US4091237  1978-05 Wolnowsky  Lockheed Missiles & Space Company, Inc. Bi-Phase harmonic histogram pitch extractor
Get PDF - 44pp US4181821  1980-01 Pirz  Bell Telephone Laboratories, Incorporated Multiple template speech recognition system
Get PDF - 22pp US4307446  1981-12 Barton  Burroughs Corporation Digital communication networks employing speed independent switches
Get PDF - 47pp US4319085  1982-03 Welch  Threshold Technology Inc. Speech recognition apparatus and method
Get PDF - 26pp US4466060  1984-08 Riddle  AT&T Bell Telephone Laboratories, Incorporated Message routing in a computer network
Get PDF - 16pp US4535473  1985-08 Sakata  Tokyo Shibaura Denki Kabushiki Kaisha Apparatus for detecting the duration of voice
Get PDF - 35pp US4759068  1988-07 Bahl et al.  International Business Machines Corporation Constructing Markov models of words from multiple utterances
Get PDF - 32pp US4827521  1989-05 Bahl et al.  International Business Machines Corporation Training of markov models used in a speech recognition system
Get PDF - 53pp US4833712  1989-05 Bahl et al.  International Business Machines Corporation Automatic generation of simple Markov model stunted baseforms for words in a vocabulary
Get PDF - 39pp US4837831  1989-06 Gillick et al.  Dragon Systems, Inc. Method for creating and using multiple-word sound models in speech recognition
Get PDF - 10pp US4852173  1989-07 Bahl et al.  International Business Machines Corporation Design and construction of a binary-tree system for language modelling
Foreign References: None

Other Abstract Info: DERABS G90-283873

Other References:
  • "An Information Theoretic Approach to the Automatic Determination of Phonemic Baseforms," J. M. Lucassen et al., Proceeding of the International Conference on Acoustics, Speech & Signal Processing, 1984, pp. 42.5.1-42.5.4.
  • "A Maximum Likelihood Approach to Continuous Speech Recognition", L. R. Bahl et al., IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 5, No. 2, Mar. 1983, pp. 170-190.
  • "Continuous Speech Recognition with Automatically Selected Acoustic Prototypes Obtained by Either Bootstrapping or Clustering," A. Nadas et al., Proceedings of the International Conference on Acoustics, Speech & Signal Processing, 1981, pp. 1153-1155.
  • "Continuous Speech Recognition by Statistical Methods," F. Jelinek, Proceedings of the IEE, vol. 64, 1976, pp. 532-556. (25 pages) Cited by 30 patents
  • "Minimum Prediction Residual Principle Applied to Speech Recognition," F. Itakura, IEE Transactions on Acoustics, Speech & Signal Processing, vol. 23, 1975, pp. 67-72. (6 pages) Cited by 22 patents

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