Spoken Emotion Recognition Using Radial Basis Function Neural Network

Recognizing human emotion from speech signals, i.e., spoken emotion recognition, is a new and interesting subject in artificial intelligence field. In this paper we present a new method of spoken emotion recognition based on radial basis function neutral networks (RBFNN). The acoustic features related to human emotion expression are extracted from speech signals and then fed into RBFNN for emotion classification. The performance of RBFNN on spoken emotion recognition task is compared with several existing methods including linear discriminant classifiers (LDC), K-nearest-neighbor (KNN), and C4.5 decision tree. The experimental results on emotional Chinese speech corpus demonstrate the promising performance of RBFNN.

[1]  Jooyoung Park,et al.  Universal Approximation Using Radial-Basis-Function Networks , 1991, Neural Computation.

[2]  Valery A. Petrushin,et al.  EMOTION IN SPEECH: RECOGNITION AND APPLICATION TO CALL CENTERS , 1999 .

[3]  Rosalind W. Picard.  Affective computing: (526112012-054) , 1997 .

[4]  George N. Votsis,et al.  Emotion recognition in human-computer interaction , 2001, IEEE Signal Process. Mag..

[5]  Shiqing Zhang,et al.  Emotion Recognition in Chinese Natural Speech by Combining Prosody and Voice Quality Features , 2008, ISNN.

[6]  Frank Dellaert,et al.  Recognizing emotion in speech , 1996, Proceeding of Fourth International Conference on Spoken Language Processing. ICSLP '96.

[7]  Ying Tan,et al.  Advances in Neural Networks - ISNN 2008, 5th International Symposium on Neural Networks, ISNN 2008, Beijing, China, September 24-28, 2008, Proceedings, Part I , 2008, ISNN.

[8]  Meng Joo Er,et al.  Face recognition with radial basis function (RBF) neural networks , 2002, IEEE Trans. Neural Networks.

[9]  Steven J. Simske,et al.  Recognition of emotions in interactive voice response systems , 2003, INTERSPEECH.

[10]  Shrikanth S. Narayanan,et al.  Toward detecting emotions in spoken dialogs , 2005, IEEE Transactions on Speech and Audio Processing.

[11]  Carlos Busso,et al.  Emotion recognition using a hierarchical binary decision tree approach , 2011, Speech Commun..

[12]  E. Vesterinen,et al.  Affective Computing , 2009, Encyclopedia of Biometrics.