Study of Speech Emotion Recognition Based on Prosodic Parameters and Facial Expression Features

Abstract:

The present status of speech emotion recognition was introduced in the paper. The emotional databases of Chinese speech and facial expressions were established with the noise stimulus and movies evoking subjects' emtion. For different emotional states, we analyzed the single-mode speech emotion recognitions based the prosodic features and the geometric features of facial expression. Then, we discussed the bimodal emotion recognition by the use of Gaussian Mixture Model. The experimental results show that, the bimodal emotion recognition rate combined with facial expression is about 6% higher than the single model recognition rate merely using prosodic features.

• Periodical: Applied Mechanics and Materials (Volumes 241-244)
• Pages: 1677-1681
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.241-244.1677
• Online since: December 2012
• Authors: Yu Tai Wang, Jie Han, Xiao Qing Jiang, Jing Zou, Hui Zhao
• Keywords: Bimodal Recognition, Facial Expression, Gaussian Mixture Model, Prosodic Features

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