An efficient use of support vector machines for speech signal classification

In this paper, we are proposing a new classifier called support vector machines to classify the speech signals. We have achieved very good generalization performance by implementing the support vector machines with various kernel functions. The use One-vs-One Classifier with voting algorithm improves speech signal classification systems efficiency.

[1]  B.A. Sonkamble,et al.  An overview of speech recognition system based on the support vector machines , 2008, 2008 International Conference on Computer and Communication Engineering.

[2]  Vladimir Vapnik,et al.  Statistical learning theory , 1998 .

[3]  Joseph Picone,et al.  Support vector machines for speech recognition , 1998, ICSLP.

[4]  Fernando Pérez-Cruz,et al.  Multi-class support vector machines: a new approach , 2003, 2003 IEEE International Conference on Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03)..

[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]  Nello Cristianini,et al.  An Introduction to Support Vector Machines and Other Kernel-based Learning Methods , 2000 .

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

[8]  Alexander J. Smola,et al.  Learning with kernels , 1998 .

[9]  Biing-Hwang Juang,et al.  Fundamentals of speech recognition , 1993, Prentice Hall signal processing series.