Universiti Teknologi Malaysia Institutional Repository

Speech emotion recognition using spectral features

Salam, Md. Sah and Mohamed Idris, Inshirah Abdelraman (2015) Speech emotion recognition using spectral features. In: International Conference on Machine Learning and Signal Processing MALSIP 2015, 15-17 Dec, 2015, Vietnam.

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Official URL: http://www.globaleventslist.elsevier.com/events/20...

Abstract

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.

Item Type:Conference or Workshop Item (Paper)
Uncontrolled Keywords:spectral features, coefficients
Subjects:Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Divisions:Computing
ID Code:61621
Deposited By: Widya Wahid
Deposited On:25 Apr 2017 06:53
Last Modified:25 Apr 2017 06:53

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