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Title: US6246982: Method for measuring distance between collections of distributions
[ Derwent Title ]

Country: US United States of America

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9 pages

Inventor: Beigi, Homayoon S. M.; Yorktown Heights, NY
Maes, Stephane H.; Danbury, CT
Sorensen, Jeffrey S.; Seymour, CT

Assignee: International Business Machines Corporation, Armonk, NY
other patents from INTERNATIONAL BUSINESS MACHINES CORPORATION (280070) (approx. 44,393)
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Published / Filed: 2001-06-12 / 1999-01-26

Application Number: US1999000237063

IPC Code: Advanced: G10L 15/10; G10L 17/00;
IPC-7: G10L 15/10; G10L 17/00;

ECLA Code: G10L17/08; G10L15/10;

U.S. Class: Current: 704/238; 704/239; 704/246; 704/E15.015; 704/E17.008;
Original: 704/238; 704/239; 704/246;

Field of Search: 704/238,239,246

Priority Number:
1999-01-26  US1999000237063

Abstract:     A method for computing a distance between collections of distributions or finite mixture models of features. Data is processed so as to define at least first and second collections of distributions of features. For each distribution of the first collection, the distance to each distribution of the second collection is measured to determine which distribution of the second collection is the closest (most similar). The same procedure is performed for the distributions of the second collection. Based on the closest distance measures, a final distance is computed representing the distance between the first and second collections. This final distance may be a weighted sum of the closest distances. The distance measure may be used in a number of applications such as [speaker classification,] speaker recognition and audio segmentation.

Attorney, Agent or Firm: F. Chau & Associates, LLP ;

Primary / Asst. Examiners: Smits, Talivaldis I.;

INPADOC Legal Status: Show legal status actions

Family: None

First Claim:
Show all 19 claims
What is claimed is:     1. A computer-implemented method for extracting audio features from audio data, comprising the steps of:
  • defining at least first and second collections of distributions of features from said data;
  • for each distribution of said first collection, determining which distribution of said second collection has the closest distance thereto, whereby a plurality of closest distances are obtained; and
  • computing a final distance between said first and second collections based at least upon said closest distances.

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Forward References: Show 14 U.S. patent(s) that reference this one

U.S. References: Go to Result Set: All U.S. references   |  Forward references (14)   |   Backward references (5)   |   Citation Link

Patent  Pub.Date  Inventor Assignee   Title
Get PDF - 14pp US5664059  1997-09 Zhao  Panasonic Technologies, Inc. Self-learning speaker adaptation based on spectral variation source decomposition
Get PDF - 17pp US5787396  1998-09 Komori et al.  Canon Kabushiki Kaisha Speech recognition method
Get PDF - 12pp US5825978  1998-10 Digalakis et al.  SRI International Method and apparatus for speech recognition using optimized partial mixture tying of HMM state functions
Get PDF - 13pp US6009390  1999-12 Gupta et al.  Lucent Technologies Inc. Technique for selective use of Gaussian kernels and mixture component weights of tied-mixture hidden Markov models for speech recognition
Get PDF - 27pp US6064958  2000-05 Takahashi et al.  Nippon Telegraph and Telephone Corporation Pattern recognition scheme using probabilistic models based on mixtures distribution of discrete distribution
Foreign References: None

Other References:
  • Thomas E. Flick, et al. "A Minimax Approach to Development of Robust Discrimination Algorithms for Multivariate Mixture Distributions," Proc. IEEE ICASSP 88, vol. 2, pp. 1264-1267, Apr. 1988.*
  • Homayoon sadr Mohammad Beigi, et al. "A Distance Measure Between Collections of Distributions and its Application to Speaker Recognition," Proc. IEEE ICASSP 98, vol. 2, pp. 753-756, May 1998.*
  • Geoff A. Jarrad, et al. "Shared Mixture Distributions and Shared Mixture Classifiers," Proc. IEEE IDC 99, pp. 335-340, Feb. 1999.

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