SVMSVM: support vector machine speaker verification methodology

Support vector machines with the Fisher and score-space kernels are used for text independent speaker verification to provide direct discrimination between complete utterances. This is unlike approaches such as discriminatively trained Gaussian mixture models or other discriminative classifiers that discriminate at the frame-level only. Using the sequence-level discrimination approach we are able to achieve error-rates that are significantly better than the current state-of-the-art on the PolyVar database.

[1]  Douglas A. Reynolds,et al.  Speaker identification and verification using Gaussian mixture speaker models , 1995, Speech Commun..

[2]  Vladimir N. Vapnik,et al.  The Nature of Statistical Learning Theory , 2000, Statistics for Engineering and Information Science.

[3]  Christopher J. C. Burges,et al.  A Tutorial on Support Vector Machines for Pattern Recognition , 1998, Data Mining and Knowledge Discovery.

[4]  Samy Bengio,et al.  Learning the decision function for speaker verification , 2001, 2001 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings (Cat. No.01CH37221).

[5]  Steve Renals,et al.  Evaluation of kernel methods for speaker verification and identification , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[6]  Gérard Chollet,et al.  Swiss PolyPhone and PolyVar: Building Databases for Speech Recognition and Speaker Verification , 1996 .

[7]  Mark J. F. Gales,et al.  Using SVMS and discriminative models for speech recognition , 2002, 2002 IEEE International Conference on Acoustics, Speech, and Signal Processing.

[8]  Mark J. F. Gales,et al.  Speech Recognition using SVMs , 2001, NIPS.

[9]  William M. Campbell,et al.  Support vector machines for speaker verification and identification , 2000, Neural Networks for Signal Processing X. Proceedings of the 2000 IEEE Signal Processing Society Workshop (Cat. No.00TH8501).

[10]  Douglas A. Reynolds,et al.  The NIST speaker recognition evaluation - Overview, methodology, systems, results, perspective , 2000, Speech Commun..

[11]  David Haussler,et al.  Exploiting Generative Models in Discriminative Classifiers , 1998, NIPS.