A kernel trick for sequences applied to text-independent speaker verification systems

Pattern Recognition

Volumn 40, Issue 8, 2007, Pages 2315-2324

  Mariéthoz, Johnny ^a,b   Bengio, Samy ^a,b  

^a IDIAP RESEARCH INSTITUTE   (Switzerland)

^b EPFL   (Switzerland)

Author keywords

Gaussian mixture models; Sequence kernel; Support vector machines; Text independent speaker verification

Indexed keywords

DATABASE SYSTEMS; ENGINEERING RESEARCH; STATISTICAL METHODS; SUPPORT VECTOR MACHINES;

GAUSSIAN MIXTURE MODELS; SEQUENCE KERNEL; TEXT-INDEPENDENT SPEAKER VERIFICATION;

SPEECH RECOGNITION;

EID: 34147189462     PISSN: 00313203     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.patcog.2007.01.011     Document Type: Article

References (22)

1. Reynolds D.A., Quatieri T.F., and Dunn R.B. Speaker verification using adapted gaussian mixture models. Digital Signal Process 10 1-3 (2000)
2. Gauvain J.L., and Lee C.-H. Maximum a posteriori estimation for multivariate Gaussian mixture observation of markov chains. IEEE Trans. Speech Audio Process. 2 (1994) 291-298
3. W. Campbell, Generalized linear discriminant sequence kernels for speaker recognition, in: Proceedings of the IEEE International Conference on Audio Speech and Signal Processing, 2002, pp. 161-164.
4. Campbell W.M., Campbell J.P., Reynolds D.A., Singer E., and Torres-Carrasquillo P.A. Support vector machines for speaker and language recognition. Comput. Speech Lang. 20 2-3 (2006) 125-127
5. A. Martin, G. Doddington, T. Kamm, M. Ordowski, M. Przybocki, The DET curve in assessment of detection task performance, in: Proceedings of Eurospeech'97, Rhodes, Greece, 1997, pp. 1895-1898.
6. S. Bengio, J. Mariéthoz, M. Keller, The expected performance curve, in: International Conference on Machine Learning, ICML, Workshop on ROC Analysis in Machine Learning, 2005.
7. S. Bengio, J. Mariéthoz, A statistical significance test for person authentication, in: Proceedings of Odyssey 2004: The Speaker and Language Recognition Workshop, 2004, pp. 237-240.
8. G. Chollet, J.-L. Cochard, A. Constantinescu, C. Jaboulet, P. Langlais, Swiss French polyphone and polyvar: telephone speech databases to model inter- and intra-speaker variability, IDIAP-RR 01, IDIAP, 1996, available at ftp://www.idiap.ch/pub/reports/1996/rr96-01.ps.gz.
9. Bailly-Baillière E., Bengio S., Bimbot F., Hamouz M., Kittler J., Mariéthoz J., Matas J., Messer K., Popovici V., Porée F., Ruiz B., and Thiran J.-P. The BANCA database and evaluation protocol. Fourth International Conference on Audio- and Video-Based Biometric Person Authentication (2003), AVBPA, Springer, Berlin 625-638
10. Rabiner L., and Juang B.-H. Fundamentals of speech recognition. first ed. (1993), Prentice-Hall, Englewood Clifts, NJ
11. Magrin-Chagnolleau I., Gravier G., and Blouet R. Overview of the 2000-2001 ELISA consortium research activities. A Speaker Odyssey (2001) 67-72
12. Vapnik V.N. The Nature of Statistical Learning Theory. second ed. (1995), Springer, Berlin
13. Joachims T. Learning to Classify Text using Support Vector Machines (2002), Kluwer Academic Publishers, Dordrecht, The Netherland
14. Pontil M., and Verri A. Support vector machines for 3-d object recognition. IEEE Trans. Patern. Anal. Mach. Intell. 20 (1998) 637-646
15. Kwok J.T.-Y. Support vector mixture for classification and regression problems. 14th International Conference on Pattern Recognition (1998)
16. Wan V., and Renals S. Speaker verification using sequence discriminant support vector machines. IEEE Trans. Speech Audio Process. 13 2 (2005) 203-210
17. Jaakkola T., and Haussler D. Exploiting generative models in discriminative classifiers. Adv. Neural Inform. Process. 11 (1998) 487-493
18. Wan V., and Renals S. Support vector machine speaker verification methodology. IEEE International Conference on Acoustic, Speech, and Signal Processing, ICASSP (2003) 221-224
19. Boughorbel S., Tarel J.P., and Fleuret F. Non-mercer kernel for svm object recognition. British Machine Vision Conference (2004)
20. Burges C. A tutorial on support vector machines for pattern recognition. Knowledge Discovery Data Min. 2 2 (1998)
21. Grandvalet Y., Mariéthoz J., and Bengio S. A probabilistic interpretation of svms with an application to unbalanced classification. Advances in Neural Information Processing Systems (2005), NIPS 15, IDIAP-RR 05-26
22. R. Collobert, S. Bengio, J. Mariéthoz, Torch: a modular machine learning software library, Technical Report IDIAP-RR 02-46, IDIAP, 2002.