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《Journal of Applied Acoustics》 2020-02
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Research on feature selection method in speech emotion recognition

CHU Yu;LI Tiangang;YE Shuo;YE Guangming;Wuhan Research Institute of Posts and Telecommunications;Wuhan Fiberhome Wisdom Digital Technology Co.Ltd.;  
Speech emotion recognition is of great value in many fields. The recognition effect of different emotion acoustic features is obviously different when different classifiers are used for classification. Acoustic features related to speech emotions include spectral features, rhythmic features and quality features. This paper proposes a method of feature fusion, which combines the features of the three acoustic features with the best recognition ability: all the features of the spectral features that are stable in the experiment and have a high recognition rate are retained, and the relevant statistics of the rhythmic features and quality features are extracted as auxiliary features and integrated into the spectral features. Experiments show that the fusion feature proposed in this paper is better than the single feature when using the same classifier for classification;when using different classifiers, the fusion feature still has better recognition ability and stable recognition performance. It has better recognition rate on three data sets and basically realizes cross-dataset recognition.
【Fund】: 湖北省科技厅2018年度湖北省技术创新专项重大项目(2018AAA063)
【CateGory Index】: TN912.34
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