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Erschienen in:
2011 | OriginalPaper | Buchkapitel
The CASIA Audio Emotion Recognition Method for Audio/Visual Emotion Challenge 2011
verfasst von : Shifeng Pan, Jianhua Tao, Ya Li
Erschienen in: Affective Computing and Intelligent Interaction
Verlag: Springer Berlin Heidelberg
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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.