Survey on speech emotion recognition: Features, classification schemes, and databases

نویسندگان

  • Moataz M. H. El Ayadi
  • Mohamed S. Kamel
  • Fakhri Karray
چکیده

Recently, increasing attention has been directed to the study of the emotional content of speech signals, and hence, many systems have been proposed to identify the emotional content of a spoken utterance. This paper is a survey of speech emotion classification addressing three important aspects of the design of a speech emotion recognition system. The first one is the choice of suitable features for speech representation. The second issue is the design of an appropriate classification scheme and the third issue is the proper preparation of an emotional speech database for evaluating system performance. Conclusions about the performance and limitations of current speech emotion recognition systems are discussed in the last section of this survey. This section also suggests possible ways of improving speech emotion recognition systems. & 2010 Elsevier Ltd. All rights reserved.

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عنوان ژورنال:
  • Pattern Recognition

دوره 44  شماره 

صفحات  -

تاریخ انتشار 2011