Study on speech emotion recognition system in E-learning

Abstract

Aiming at emotion deficiency in present E-Learning system, speech emotion recognition system is proposed in the paper. A corpus of emotional speech from various subjects, speaking different languages is collected for developing and testing the feasibility of the system. The potential prosodic features are first identified and extracted from the speech data. Then we introduce a systematic feature selection approach which involves the application of Sequential Forward Selection (SFS) with a General Regression Neural Network (GRNN) in conjunction with a consistency-based selection method. The selected features are employed as the input to a Modular Neural Network (MNN) to realize the classification of emotions. Our simulation experiment results show that the proposed system gives high recognition performance. © Springer-Verlag Berlin Heidelberg 2007.