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Line spectral frequencies and energy features in a robust signal recognition system

Patent 6009391 Issued on December 28, 1999. Estimated Expiration Date: Icon_subject August 6, 2017. Estimated Expiration Date is calculated based on simple USPTO term provisions. It does not account for terminal disclaimers, term adjustments, failure to pay maintenance fees, or other factors which might affect the term of a patent.

Patent References

Method and apparatus for speech recognition
Patent #: 4383135
Issued on: 05/10/1983
Inventor: Scott ,   et al.

LPC Word recognizer utilizing energy features
Patent #: 4519094
Issued on: 05/21/1985
Inventor: Brown ,   et al.

Apparatus and methods for the selective addition of noise to templates employed in automatic speech recognition systems
Patent #: 4933973
Issued on: 06/12/1990
Inventor: Porter

Pattern matching vocoder using LSP parameters
Patent #: 4975955
Issued on: 12/04/1990
Inventor: Taguchi

Speech recognition system using Markov models having independent label output sets
Patent #: 5031217
Issued on: 07/09/1991
Inventor: Nishimura

Adaptation of acoustic prototype vectors in a speech recognition system
Patent #: 5046099
Issued on: 09/03/1991
Inventor: Nishimura, ;, , , --> Nishimura

Noise reduction system using neural network
Patent #: 5185848
Issued on: 02/09/1993
Inventor: Aritsuka, et al.

Speech recognition apparatus and methods
Patent #: 5228087
Issued on: 07/13/1993
Inventor: Bickerton

Low bit rate vocoder means and method
Patent #: 5255339
Issued on: 10/19/1993
Inventor: Fette, et al.

Neural networks for acoustical pattern recognition
Patent #: 5285522
Issued on: 02/08/1994
Inventor: Mueller

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Inventors

Assignee

Application

No. 907145 filed on 08/06/1997

US Classes:

704/243, Creating patterns for matching704/222, Vector quantization704/236, Specialized equations or comparisons704/238Distance

Examiners

Primary: Hudspeth, David
Assistant: Storm, Donald L.

Attorney, Agent or Firm

International Class

G01L 005/06

Abstract

One embodiment of a speech recognition system is organized with speech input signal preprocessing and feature extraction followed by a fuzzy matrix quantizer (FMQ). Frames of the speech input signal are represented in a matrix by a vectorf of line spectral pair frequencies and energy coefficients and are fuzzy matrix quantized to respective vector f entries of a matrix codeword in a codebook of the FMQ. The energy coefficients include the original energy and the first and second derivatives of the original energy which increase recognition accuracy by, for example, being generally distinctive speech input signal parameters and providing noise signal suppression especially when the noise signal has a relatively constant energy over at least two time frame intervals. To reduce data while maintaining sufficient resolution, the energy coefficients may be normalized and logarithmically represented. A distance measure between f and f, d(f, f), is defined as ##EQU1## where the constants 댑, 댒, 댡 and 댢 are set to substantially minimize quantization error, ei is the error power spectrum of the speech input signal and a predicted speech input signal at the ith line spectral pair frequency of the speech input signal, the first G LSP frequencies are most likely to be frequency shifted by noise, and the last P+3 coefficients represent the three energy coefficients. This robust distance measure can be used to enhance speech recognition performance in generally any speech recognition system using line spectral pair based distance measures.

Other References

  • Rabiner, Lawrence and Juang, Biing-Hwang; "Fundamentals of Speech Recognition" 1993; pp. 190-195
  • Xydeas, C.S. Prof. and Cong, Lin "Robust Speech Recognition Using Fuzzy Matrix Quantisation, Neural Networks and Hidden Markov Models" Sep. 1996, pp. 1587-1590
  • Cong, Ling, Xydeas, Costas S. Prof. and Ferwood, Anthony F. Combining Fuzzy Vector Quantisation and Neural Network Classification for Robust Isolated Word Speech Recognition: Singapore ICCS 1994, pp. 884-887
  • Parsons, Thomas W,; "Voice and Speech Processing"; McGraw-Hill, Inc., New York, 1987; pp. 170-171
  • Xydeas, C.S. and Lin Cong; "Robust Speech Recognition Using Fuzzy Matrix Quantization and Neural Networks"; Proceedings of International Conference on Communication Technology; Beijing, China -ICCT '96; pp. 432-435; IEEE; New York (May 5-7,1996)
  • Cong, Lin; "A Study of Robust IWSR Systems"; PhD Thesis submitted to The University of Manchester School of Engineering, Division of Electrical Engineering; Manchester, United Kingdom; pp. 1-209, May 1996
  • Waibel, Alexander; "Neural Network Approaches for Speech Recognition"; Chapter 18 of Advances in Speech Signal Processing; edited by Sadaoki Furui and M. Mohan Sondhi; Marcel Dekker, Inc. ; New York, New York; 1992; pp. 555-595
  • Xydeas, C.S. and Cong, L.; "Combining Neural Network Classification with Fuzzy Vector Quantization and Hidden Markov Models for Robust Isolated Word Speech Recognition"; Signal Processing VIII Theories and Applications, vol. III; Proceedings of the IEEE International Symposium on Information Theory IEEE Press, 1995, p.174
  • Xydeas, C.S. and Cong, L; "Robust Speech Recognition in A Car Environment"; Presented at DSP95 International Conference on Digital Signal Processing, Jun. 26-28, 1995, Limassol, Cyprus; vol. 1, pp. 84-89
  • Cong, Lin, Prof. C.S. Xydeas, and Anthony Ferwood; "A Study of Robust Isolated Word Speech Recognition Based on Fuzzy Methods"; Presented at EUSIPCO-94, VII European Signal Processing Conference, Sep. 13-16, 1994; Scotland, UK.; 4 pages
  • Gibson, Jerry D.; "Coding, Transmission, and Storage"; Chapter 14, Speech Signal Processing, ofThe Electrical Engineering Handbook; Editor-in-Chief Richard C. Dorf; .COPYRGT.1993 by CRC Press, Inc.; pp. 279-314
  • Gersho, Allen and Shihua Wang; "Vector Quantization Techniques in Speech Coding"; Chapter 2 of Advances in Speech Signal Processing; edited by Sadoki Furui and Mohan Sondhi; Marcel Dekker, Inc.; New York, New York; 1992; pp.49-84
  • Kroon, Peter and Bishnu S. Atal; "Predictive Coding of Speech Using Analysis-by-Synthesis Techniques"; Chapter 5 of Advances in Speech Signal Processing; edited by Sadaoki Furui and M. Mohan Sondhi; Marcel Dekker, Inc.; New York, New York; 1992; pp. 141-164
  • Honda, Masaaki and Yoshinao Shiraki; "Very Low-Bit-Rate Speech Coding"; Chapter 7 of Advances in Speech Signal Processing; edited by Sadaoki Furui and M. Mohan Sondhi; Marcel Dekker, Inc.; New York, New York; 1992; pp. 209-230
  • Schroeter, Juergen and M. Mohan Sondhi; "Speech Coding Based on Physiological Models of Speech Production"; Chapter 8 of Advances in Speech Signal Processing; edited by Sadaoki Furui and M. Mohan Sondhi; Marcel Dekker, Inc.; New York, New York; 1992; pp. 231-26
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