Study on speech emotion recognition system in E-learning

Authors:
Aiqin Zhu;Qi Luo
Affiliations:
College of Urban and Environment Science, Central China Normal University, Wuhan, Hubei, China;Wuhan University of Science and Technology, Wuhan, Hubei, China
Venue:
HCI'07 Proceedings of the 12th international conference on Human-computer interaction: intelligent multimodal interaction environments
Year:
2007

Citing 2
Cited 3

Affective computing

Affective computing
Affective computing: challenges

International Journal of Human-Computer Studies - Application of affective computing in human—Computer interaction

Emotion recognition from speech: a review

International Journal of Speech Technology
Emotion recognition from speech using source, system, and prosodic features

International Journal of Speech Technology
Emotion recognition from speech using global and local prosodic features

International Journal of Speech Technology

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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.