¹School of Mechatronical Engineering & Automation, Shanghai University, Shanghai
²State Key Laboratory of Robotics and System, HIT
³Shanghai Key Laboratory of Power Station Automation Technology

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Abstract—Speech emotion recognition is an important issue in the development of human-computer interactions. In this paper a series of novel robust features for speech emotion recognition is proposed. Those features, which derived from the Hilbert-Huang transform (HHT) and Teager energy operator (TEO), have the characteristics of multi-resolution, self-adaptability and high precision of distinguish ability. In the experiments, seven status of emotion were selected to be recognized and the highest 85% recognition rate was achieved within the classification accuracy of boredom reached up to 100%. The numerical results indicate that the proposed features are robust and the performance of speech emotion recognition is improved substantially.

Index Terms—HHT, Signal trend, Teager energy operator, instantaneous frequency, speech emotion recognition

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Cite: Xiang Li, Xin Li , "Speech Emotion Recognition Using Novel HHT-TEO Based Features," Journal of Computers vol. 6, no. 5, pp. 989-998, 2011.