关键词: 相空间重构, Kolmogorov熵, 关联维, 情感识别

Abstract: In order to express the sound emotion state totally, make up the inadequate of emotional conventional linear argument at depicting different types of character sentiments, this paper takes the phase space reconstruction theory into the sound emotional identification, by analyzing chaotic features on the different sound emotional states, proposes correlation dimension and Kolmogorov entropy as emotional characteristic parameters, combines with traditional voice acoustic features and uses Support Vector Machine（SVM） for speech emotion recognition. The results show that recognition accuracy is improved through using chaotic characteristic parameters, providing a new research approach for speech emotion recognition.

Key words: phase space reconstruction, Kolmogorov entropy, correlation dimension, emotion recognition