[1] Wang Zhiping, Zhao Li, Zou Cairong,. Support vector machines for emotion recognitionin Chinese speech [J]. Journal of Southeast University (English Edition), 2003, 19 (4): 307-310. [doi:10.3969/j.issn.1003-7985.2003.04.001]

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Support vector machines for emotion recognitionin Chinese speech()

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Journal of Southeast University (English Edition)[ISSN:1003-7985/CN:32-1325/N]

Volumn:

19

Issue:

2003 4

Page:

307-310

Research Field:

Information and Communication Engineering

Publishing date:

2003-12-30

Info

Title:

Support vector machines for emotion recognitionin Chinese speech

Author(s):

Wang Zhiping;  Zhao Li;  Zou Cairong

Department of Radio Engineering, Southeast University, Nanjing 210096, China

Keywords:

speech signal;  emotion recognition;  support vector machines

PACS:

TN912.34

DOI:

10.3969/j.issn.1003-7985.2003.04.001

Abstract:

Support vector machines(SVMs)are utilized for emotion recognition in Chinese speech in this paper. Both binary-class discrimination and the multi-class discrimination are discussed. It proves that the emotional features construct a nonlinear problem in the input space, and SVMs based on nonlinear mapping can solve it more effectively than other linear methods. Multi-class classification based on SVMs with a soft decision function is constructed to classify the four emotion situations. Compared with principal component analysis(PCA)method and modified PCA method, SVMs perform the best result in multi-class discrimination by using nonlinear kernel mapping.

References:

[1] Vapnik V N. Statistical learning theory [M]. New York: Wiley, 1998.
[2] Christopher, Burges C J C. A tutorial on support vector machines for pattern recognition [J]. Data Mining and Knowledge, 1998, 2(2):121-167.
[3] Platt J. Sequential minimal optimization: a fast algorithm for training support vector machines [R]. Microsoft Research Technical Report MSR-TR-98-14, 1998.
[4] Crammer K, Singer Y. On the learn ability and design of output codes for multiclass problems [A]. In: Proceeding of the Thirteenth Annual Conference on Computational Learning Theory [C]. 2000.35-46.
[5] Weston J, Watkins C. Multi-class support vector machines[A]. In: Verleysen M, ed. Proc ESANN99[C]. Brussels, Belgium, 1999.
[6] Hsu Chih-Wei, Lin Chih-Jen. A comparison of methods for multiclass support vector machines [J]. IEEE Trans Neural Networks, 2002, 13(2): 415-425.
[7] Zhao Li, Qian Xiangmin, Zou Cairong, et al. A study on emotional feature analysis and recognition in speech signal [J]. Journal of China Institute of Communication, 2000, 21(10):18-24.(in Chinese)

Memo

Memo:

Biographies: Wang Zhiping(1977—), male, graduate; Zou Cairong(corresponding author), male, doctor, professor, cairong@seu.edu.cn.

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