关键词: 经验模态分解（EMD）, 特征提取, 支持向量机（SVM）, 情感识别

Abstract: In recent years, extensive concern about calculated speech emotion has been aroused at home and abroad. Especially, a lot of studies have been done in speech emotion feature extraction. The Intrinsic Mode Function（IMF） for the first four steps of the emotion speech is attained in this paper by using the method of Empirical Mode Decomposition（EMD） to process the emotion speech. And the instantaneous frequency and amplitude of the Intrinsic Mode Function（IMF） for the first four steps are got by Hilbert transformation respectively. The emotion characteristics vector is composed by extracting their statistical characteristics and combining the acoustic characteristics of emotion speech and characteristics vector is normalized. The four kinds of emotion speech, namely angry, happiness, sadness and calmness are recognized by using the Support Vector Machine（SVM）. Experimental results show that the recognition effect of this proposed method is much better.

Key words: Empirical Mode Decomposition（EMD）, feature extraction, Support Vector Machine（SVM）, emotion recognition