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A new recognition method based on Gaussian mixture model for speech emotion recognition is proposed in this paper. To improve the effectiveness of feature extraction and accuracy of emotion recognition, extraction of Mel frequency cepstrum coefficient combined with Gaussian mixture model is used to recognize speech emotion. According to feature parameters extraction method by analyzing the principle of vocalization theory, emotion models based on Gaussian mixture model are generated and the similarity of their templates is obtained. A series of experiments is performed with recorded speech based on Gaussian mixture model and indicates the system gains high performance and better robustness.
Zhang et al. (Wed,) studied this question.