Close-Class-Set Discrimination Method for Recognition of Stop_Consonant-Vowel Utterances Using Support Vector Machines

5In conventional approaches for multi-class pattern recognition using Support Vector Machines (SVMs), each class is discriminated against all the other classes to build an SVM for that class. We propose a close-class-set discrimination method suitable for large class set pattern recognition problems. The proposed method is demonstrated for recognition of isolated utterances belonging to 80 Stop Consonant-Vowel (SCV) classes. In this method, an SVM is built for each SCV class by discriminating that class against only 10 classes close to it phonetically.

[1]  Pedro J. Moreno,et al.  On the use of support vector machines for phonetic classification , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[2]  B. Yegnanarayana,et al.  Recognition of Stop-Consonant-Vowel (SCV) segments in continuous speech using neural network models , 1996 .

[3]  Samy Bengio,et al.  SVMTorch: Support Vector Machines for Large-Scale Regression Problems , 2001, J. Mach. Learn. Res..

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

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

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

[7]  Partha Niyogi,et al.  Distinctive feature detection using support vector machines , 1999, 1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258).

[8]  Jason Weston,et al.  Multi-Class Support Vector Machines , 1998 .