The CASIA audio emotion recognition method for audio/visual emotion challenge 2011

Authors:
Shifeng Pan;Jianhua Tao;Ya Li
Affiliations:
National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China;National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing, China
Venue:
ACII'11 Proceedings of the 4th international conference on Affective computing and intelligent interaction - Volume Part II
Year:
2011

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Abstract

This paper introduces the CASIA audio emotion recognition method for the audio sub-challenge of Audio/Visual Emotion Challenge 2011 (AVEC2011). Two popular pattern recognition techniques, SVM and AdaBoost, are adopted to solve the emotion recognition problem. The feature set is also simply investigated by comparing the performance of classifier built on the baseline feature set and the dimension reduced feature set. Experimental results show that the baseline feature set is better for the classification of arousal and power dimensions, while the reduced feature set is better for the other affective dimensions, and the average performance of AdaBoost slightly outperforms SVMs in our experiment.