Research on Speech Emotion Recognition in E-learning System
Emotion deficiency research in E-learning is a very hot topic in current distanced education. Aiming at emotion deficiency in present E-Learning system, speech emotion recognition system is proposed and introduced 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 with a General Regression Neural Network in conjunction with a consistencybased selection method. The selected features are employed as the input to a Modular Neural Network to realize the classification of emotions. After the test of speech emotion recognition system, the result manifests that the system is effective.
e-learning SFS GRNN, MNN, affective computing
LUO Qi TAN Honghua
School of Electrical Engineering, Wuhan Institute of technology, Wuhan 430073, China;Department of I School of Electrical Engineering, Wuhan Institute of technology, Wuhan 430073, China
国际会议
武汉
英文
173-176
2007-07-25（万方平台首次上网日期，不代表论文的发表时间）