Using post-classifiers to enhance fusion of low- and high-level speaker recognition

IEEE Transactions on Audio, Speech and Language Processing

Volumn 15, Issue 7, 2007, Pages 2063-2071

  Solewicz, Yosef A ^a   Koppel, Moshe ^a  

^a BAR ILAN UNIVERSITY   (Israel)

Author keywords

Fusion; Machine learning; Post classification; Speaker recognition

Indexed keywords

FUSION; MACHINE LEARNING; POST-CLASSIFICATION; RELATIVE PERFORMANCE; SPEAKER RECOGNITION; SPEAKER RECOGNITION SYSTEMS; STATE-OF-THE-ART SYSTEMS; TRAINING AND TESTING;

CLASSIFIERS; ROBOT LEARNING;

SPEECH RECOGNITION;

EID: 64249133832     PISSN: 15587916     EISSN: None     Source Type: Journal    
DOI: 10.1109/TASL.2007.903054     Document Type: Article

References (19)

1. W. Andrews, M. A. Kohler, J. P. Campbell, and J. J. Godfrey, "Phonetic, idiolectal and acoustic speaker recognition," in Proc. ODYSSEY- 2001, Crete, Greece, 2001, pp. 55-63.
2. J. Campbell, D. Reynolds, and R. Dunn, "Fusing high- and low-level features for speaker recognition," in Proc. 8th Eur. Conf. Speech Commun. Technol. (Eurospeech), Geneva, Switzerland, 2003, pp. 2665-2668.
3. D. Reynolds, W. Andrews, J. Campbell, J. Navratil, B. Peskin, A. Adami, Q. Jin, D. Klusacek, J. Abramson, R. Mihaescu, J. Godfrey, D. Jones, and B. Xiang, "The SuperSID project: Exploiting high-level information for high-accuracy speaker recognition," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), Hong Kong, China, 2003, pp. 784-787.
4. Y. Solewicz and M. Koppel, "Enhanced fusion methods for speaker verification," in Proc. 9th Int. Conf. Speech Comput. (SPECOM'04), St. Petersburg, Russia, 2004, pp. 388-392.
5. L. Ferrer, K. Sonmez, and S. Kajarekar, "Class-dependent score combination for speaker recognition," in Proc. 9th Eur. Conf. Speech Commun. Technol. (Eurospeech), Lisbon, Portugal, 2005, pp. 2173-2176.
6. Y. Solewicz and M. Koppel, "Considering speech quality in speaker verification fusion," in Proc. 9th Eur. Conf. Speech Commun. Technol. (Eurospeech), Lisbon, Portugal, 2005, pp. 2189-2192.
7. Y. Solewicz and M. Koppel, "Automatically correcting bias in speaker recognition systems," in Proc. 16th IEEE Workshop Mach. Learn. Signal Process. (MLSP'2006), Maynooth, U.K., 2006, pp. 187-191.
8. S. Furui, "Cepstral analysis technique for automatic speaker verification," IEEE Trans. Acoust. Speech Signal Process., vol. ASSP-29, no. 2, pp. 254-272, Apr. 1981.
9. H. Hermansky and N. Morgan, "RASTA processing of speech," IEEE Trans. Speech Audio Process., vol. 2, no. 4, pp. 578-589, Oct. 1994.
10. O. Viikki and K. Lurila, "Cepstral domain segmental feature vector normalization for noise robust speech recognition," Speech Commun., vol. 25, pp. 133-147, 1998.
11. J. Pelecanos and S. Sridharan, "Feature warping for robust speaker verification," in Proc. ODYSSEY-2001, Crete, Greece, 2001, pp. 213-218.
12. D. A. Reynolds, "Channel robust speaker verification via feature mapping," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), Minneapolis, MN, 2003, pp. 53-56.
13. F. Bimbot et al., "A tutorial on text-independent speaker verification," EURASIP J. Appl. Signal Process., vol. 2004, no. 4, pp. 430-451, 2004.
14. P. Kenny and P. Dumouchel, "Experiments in speaker verification using factor analysis likelihood ratios," in Proc. Odyssey: Speaker Lang. Recognition Workshop, Toledo, Spain, 2004, pp. 219-226.
15. A. Solomonoff, C. Quillen, and W. M. Campbell, "Channel compensation for SVM speaker recognition," in Proc. Odyssey: Speaker Lang. Recognition Workshop, Toledo, Spain, 2004, pp. 57-62.
16. NIST, "NIST-Speaker Recognition Evaluations." [Online]. Available: http://www.nist.gov/speech/tests/spk
17. L. Ferrer, E. Shriberg, S. S. Kajarekar, A. Stolcke, K. Sonmez, A. Venkataraman, and H. Bratt, "The contribution of cepstral and stylistic features to SRI's 2005 NIST speaker recognition evaluation system," in Proc. Int. Conf. Acoust., Speech, Signal Process. (ICASSP), Toulouse, France, 2006, pp. 101-104.
18. T. Joachims, , B. Schölkopf, C. Burges, and A. Smola, Eds., "Making large-scale SVM learning practical," in Advances in Kernel Methods-Support Vector Learning. Cambridge, MA: MIT Press, 1999.
19. D. A. van Leeuwen, A. F. Martin, M. A. Przybocki, and J. S. Bouten, "NIST and NFI-TNO evaluation on automatic speaker recognition," Comput. Speech Lang., vol. 20, pp. 128-158, 2005.