Publication Type : Conference Paper
Publisher : Proceedings - 2014 5th International Symposium on Electronic System Design, ISED 2014
Source : Proceedings - 2014 5th International Symposium on Electronic System Design, ISED 2014, Institute of Electrical and Electronics Engineers Inc., p.217-218 (2014)
Keywords : Emotion recognition, Empirical Mode Decomposition, Hilbert Huang transforms, Human computer interaction, Instantaneous frequency, Intrinsic Mode functions, Mathematical transformations, Signal processing, Speech recognition, Systems analysis, TEO
Campus : Bengaluru
School : School of Engineering
Department : Electronics and Communication
Year : 2014
Abstract : 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.
Cite this Research Publication : S. Lalitha, 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.