Speech Emotion Feature Selection Method Based on Contribution Analysis Algorithm of Neural Network

There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution an...

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Bibliographic Details
Published inAIP conference proceedings Vol. 1060; no. 1; pp. 336 - 339
Main Authors Wang, Xiaojia, Mao, Qirong, Zhan, Yongzhao
Format Journal Article
LanguageEnglish
Published United States 01.01.2008
Subjects
ALGORITHMS
ARTIFICIAL INTELLIGENCE
GENERAL AND MISCELLANEOUS//MATHEMATICS, COMPUTING, AND INFORMATION SCIENCE
MATHEMATICAL METHODS AND COMPUTING
NEURAL NETWORKS
SPEECH
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ISBN0735405905
9780735405905
ISSN0094-243X
1551-7616
DOI10.1063/1.3037087

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Summary:There are many emotion features. If all these features are employed to recognize emotions, redundant features may be existed. Furthermore, recognition result is unsatisfying and the cost of feature extraction is high. In this paper, a method to select speech emotion features based on contribution analysis algorithm of NN is presented. The emotion features are selected by using contribution analysis algorithm of NN from the 95 extracted features. Cluster analysis is applied to analyze the effectiveness for the features selected, and the time of feature extraction is evaluated. Finally, 24 emotion features selected are used to recognize six speech emotions. The experiments show that this method can improve the recognition rate and the time of feature extraction.
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ISBN:0735405905
9780735405905
ISSN:0094-243X
1551-7616
DOI:10.1063/1.3037087