Features Extraction And Selection In Emotional Speech

Zhongzhe Xiao 1 Emmanuel Dellandréa 1 Weibei Dou 2 Liming Chen 1
1 LIRIS - Laboratoire d'InfoRmatique en Image et Systèmes d'information
2 TNLIST - Tsinghua National Laboratory for Information Science and Technology, Department of Electronic Engineering, Tsinghua University, Beijing.
Abstract : The classification of emotional speech is a topic in speech recognition with more and more interest, and it has giant prospect in applications in a wide variety of fields. It is an important preparation for automatic classification and recognition of emotions to select a proper feature set as a description to the emotional speech, and to find a proper definition to the emotions in speech. The speech samples used in this paper come from Berlin database which contains 7 kinds of emotions, with 207 speech samples of male voice and 287 speech samples of female voice. A feature set of 50 potentially features is extracted and analyzed, and the best features are selected. A definition of emotions as 3-states emotions is also proposed in this paper.
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Conference papers
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https://hal.archives-ouvertes.fr/hal-01589300
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Submitted on : Monday, September 18, 2017 - 2:19:11 PM
Last modification on : Thursday, November 21, 2019 - 2:16:34 AM

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Zhongzhe Xiao, Emmanuel Dellandréa, Weibei Dou, Liming Chen. Features Extraction And Selection In Emotional Speech. International Conference on Advanced Video and Signal based Surveillance, AVSS 2005, Sep 2005, Como, Italy. pp.411-416, ⟨10.1109/AVSS.2005.1577304⟩. ⟨hal-01589300⟩

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