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    Abstract:

    In this paper, some methods are proposed to discriminate utterances from the speech signal. A corpus containing emotional speech of happiness, anger, surprise and sorrow with over 300 utterances from five speakers is recorded. Ten emotional features are extracted from the speech signal. Three emotion recognition methods are introduced based on principal component analysis. Using these methods, recognition performance is obtained, which is close to human performance on the task.

    Reference
    [1] Niimi, Y. Emotional Robot World. Tokyo: Talk and Speak Press, 1995. 67~96.
    [2] Muraka, S. Emotional constituents in text and emotional components in speech [Ph.D. Thesis]. Kyoto: Kyoto Institute of Technology, 1998.
    [3] Kawanami, H. Considerations on the prosodic features of utterances with attitudes and emotions. Technical Report, sp97', Kokyo: Institute of Electronics, Information and Communication Engineers, 1997.
    [4] Cowie, R., Douglas, E. Automatic statistical analysis of the signal and prosodic signs of emotion in speech. In: IEEE ed. Proceedings of the 14th International Congress of Phonetic Sciences, Vol 3. San Francisco: Academic Press, 1999. 2327~2330.
    [5] Zhao, Li, Kobayashi, Y., Niimi, Y. Tone recognition of Chinese continuous speech using continuous HMMs. Journal of the Acoustical Society of Japan, 1997,53(12):933~940.
    [6] 周迪伟.计算机语音处理.北京:国防工业出版社,1987.130~146.
    [7] 王学仁,王松桂.实用多元统计分析.上海:上海科学技术出版社,1995.150~187.
    [8] 唐守正.多元统计方法.北京:中国林业出版社,1987.20~37.
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赵力,钱向民,邹采荣,吴镇扬.语音信号中的情感识别研究.软件学报,2001,12(7):1050-1055

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History
  • Received:October 15,1999
  • Revised:March 23,2000
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