Speech emotion recognition using spectral features
In order to improve the performance of the speech emotion recognition system and reduce the computing complexity, a speech emo- tion recognition based on optimized coefficients number for spectral fea- tures is proposed. Experimental studies are performed over the Berlin emotional Database, using su...
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| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Published: |
2015
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| Subjects: | |
| Online Access: | http://eprints.utm.my/id/eprint/61621/ http://www.globaleventslist.elsevier.com/events/2015/12/machine-learning-and-signal-processing-international-conference/ |
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| Institution: | Universiti Teknologi Malaysia |
| Summary: | In order to improve the performance of the speech emotion recognition system and reduce the computing complexity, a speech emo- tion recognition based on optimized coefficients number for spectral fea- tures is proposed. Experimental studies are performed over the Berlin emotional Database, using support vector machine (SVM) classifier and five spectral features MFCC, LPC, LPCC, PLP, and PLP-RASTA. The experiment result shows that the speech emotion recognition based on coefficients number can improve the performance of the emotion recog- nition system effectively. abstract environment. |
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