A study of speech emotion recognition based on hybrid algorithm

Ju-xia Zhu; Chao Zhang; Zhao Lv; Yao-quan Rao; Xiao-pei Wu

doi:10.1117/12.913366

1 October 2011 A study of speech emotion recognition based on hybrid algorithm

Ju-xia Zhu, Chao Zhang, Zhao Lv, Yao-quan Rao, Xiao-pei Wu

Proceedings Volume 8285, International Conference on Graphic and Image Processing (ICGIP 2011); 82854Y (2011) https://doi.org/10.1117/12.913366
Event: 2011 International Conference on Graphic and Image Processing, 2011, Cairo, Egypt

Abstract

To effectively improve the recognition accuracy of the speech emotion recognition system, a hybrid algorithm which combines Continuous Hidden Markov Model (CHMM), All-Class-in-One Neural Network (ACON) and Support Vector Machine (SVM) is proposed. In SVM and ACON methods, some global statistics are used as emotional features, while in CHMM method, instantaneous features are employed. The recognition rate by the proposed method is 92.25%, with the rejection rate to be 0.78%. Furthermore, it obtains the relative increasing of 8.53%, 4.69% and 0.78% compared with ACON, CHMM and SVM methods respectively. The experiment result confirms the efficiency of distinguishing anger, happiness, neutral and sadness emotional states.

Citation Download Citation

Ju-xia Zhu, Chao Zhang, Zhao Lv, Yao-quan Rao, and Xiao-pei Wu "A study of speech emotion recognition based on hybrid algorithm", Proc. SPIE 8285, International Conference on Graphic and Image Processing (ICGIP 2011), 82854Y (1 October 2011); https://doi.org/10.1117/12.913366

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