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Reseach Article

Speaker Recognition Using Auditory Features and Polynomial Classifier

by Pawan K. Ajmera, Raghunath S. Holambe
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 1 - Number 14
Year of Publication: 2010
Authors: Pawan K. Ajmera, Raghunath S. Holambe
10.5120/294-458

Pawan K. Ajmera, Raghunath S. Holambe . Speaker Recognition Using Auditory Features and Polynomial Classifier. International Journal of Computer Applications. 1, 14 ( February 2010), 86-91. DOI=10.5120/294-458

@article{ 10.5120/294-458,
author = { Pawan K. Ajmera, Raghunath S. Holambe },
title = { Speaker Recognition Using Auditory Features and Polynomial Classifier },
journal = { International Journal of Computer Applications },
issue_date = { February 2010 },
volume = { 1 },
number = { 14 },
month = { February },
year = { 2010 },
issn = { 0975-8887 },
pages = { 86-91 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume1/number14/294-458/ },
doi = { 10.5120/294-458 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T19:42:16.822900+05:30
%A Pawan K. Ajmera
%A Raghunath S. Holambe
%T Speaker Recognition Using Auditory Features and Polynomial Classifier
%J International Journal of Computer Applications
%@ 0975-8887
%V 1
%N 14
%P 86-91
%D 2010
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents a speaker recognition method which makes use of auditory features and polynomial classifier for speaker recognition. Auditory features based on an auditory periphery model extract significant speaker characteristics. Polynomial classifier has been used to accomplish speaker recognition task. Polynomial classifier has several advantages over the conventional classifiers such as computational scalability with the number of speakers, discriminative training allowing it to use out of class data and the statistical interpretation of scoring allowing it to combine with HMM and GMM. This approach achieves substantial performance improvement in a speaker identification task compared with state-of-the-art in a wide range of signal to noise conditions.

References
  1. Campbell W. M., Assaleh K. T. and Broun C. C., 2002, Speaker recognition with polynomial classifiers, IEEE Trans. on Speech and Audio Processing, 10 (4), 205-212.
  2. Carey M. J., Parris E. S, and Bridle J. S., 1991, A speaker verification system using alpha-nets, in Proc. Int. Conf. Acoustics, Speech, Signal Processing, , 397-400.
  3. Davis S. B. and Mermelstein P., 1980, Comparison of parametric representations for monosyllabic word recognition in continuously spoken sentences, IEEE Trans. ASSP, 28(4), 357-366.
  4. Farrell K. R., Mammone R. J., and Assaleh K. T., 1994, Speaker recognition using neural networks and conventional classifiers, IEEE Trans. Speech Audio Processing, 2, 194-205.
  5. Ghitza O., 1994, Auditory models and human performance in tasks related to speech coding and speech recognition, IEEE Trans. SAP, 2 (1), 115-132.
  6. Glasberg B. R. and Moore B. C. J., 1990, Derivation of auditory filter shapes from notched-noise data, Hear. Res., 47, 103-138.
  7. Hermansky H., 1990, Perceptual linear predictive (PLP) analysis of speech, J. Acoust. Soc. Am., 87(4), 1738-1752.
  8. Hermansky H. and Morgan N., 1994, RASTA processing of speech, IEEE Trans. SAP, 2 (4), 578-589.
  9. Higgins A., Bahler L., and Porter J., 1991, Speaker verification using randomized phrase prompting, Digital Signal Process., 1, 89- 106.
  10. Irino T. and Patterson R. D., 1997, A time-domain, level- dependent auditory filter: the gammachirp, J. Acoust. Soc. Am., 101, 412-419.
  11. Shao Y. and. Wang D. L, 2006, Robust speaker recognition using binary time-frequency masks, in Proc. ICASSP, 1, 645-648.
  12. Skowronski M. D. and Harris J. G., 2002, Increased MFCC filter bandwidth for noise-robust phoneme recognition, in Proc. ICASSP-02, Florida.
  13. Reynolds D. A., 1995, Automatic speaker recognition using Gaussian mixture speaker models, Lincoln Lab. J., 8( 2), 173-192.
  14. Rosenberg A. E., DeLong J., Lee C.-H., Juang B.-H., and Soong F. K., 1992, the use of cohort normalized scores for speaker verification, in Proc. Int. Conf. Spoken Language Processing, 599-602.
  15. Rosenberg A. E. and Parthasarathy S., 1996, Speaker background models for connected digit password speaker verification, in Proc. Int. Conf. Acoustics, Speech, Signal Processing, 81-84.
  16. Yoma N. B. and Villar M., 2002, Speaker verification in noise using a stochastic version of the weighted Viterbi algorithm, IEEE Trans. Speech Audio Process., 10(3), 158.
Index Terms

Computer Science
Information Sciences

Keywords

Speaker recognition Auditory features Polynomial classifier