This paper aims at developing a Speaker Emotion Recognition (SER) system to recognize seven different emotions namely anger, boredom, fear, disgust, happiness, neutral and sadness with a generalized feature set in real-time. Continuous HMM and LIBSVM classifiers are considered in this paper. The choice of LIBSVM classifier provides better recognition rates for few emotions (Anger and Fear) compared to the Continuous HMM classifier used in the earlier work by Xiang Li. The Hilbert-Huang transform (HHT) and Teager Energy Operator (TEO) based features gives the advantage of self-adaptability and hence can be used for real time applications. © 2014 IEEE.
cited By 0; Conference of 5th International Symposium on Electronic System Design, ISED 2014 ; Conference Date: 15 December 2014 Through 17 December 2014; Conference Code:115765
L. S., S., P., T.H., A., V., M., and S., T., “Emotion Recognition through Speech Signal for Human-Computer Interaction”, in Proceedings - 2014 5th International Symposium on Electronic System Design, ISED 2014, 2014, pp. 217-218.