Two-level discriminative speech emotion recognition model with wave field dynamics: A personalized speech emotion recognition method

Author(s):  
Ning Jia ◽  
Chunjun Zheng
2020 ◽  
Vol 140 ◽  
pp. 358-365
Author(s):  
Zijiang Zhu ◽  
Weihuang Dai ◽  
Yi Hu ◽  
Junshan Li

2014 ◽  
Vol 668-669 ◽  
pp. 1126-1129
Author(s):  
Wan Li Zhang ◽  
Guo Xin Li ◽  
Wei Gao

A new recognition method based on Gaussian mixture model for speech emotion recognition is proposed in this paper. To improve the effectiveness of feature extraction and accuracy of emotion recognition, extraction of Mel frequency cepstrum coefficient combined with Gaussian mixture model is used to recognize speech emotion. According to feature parameters extraction method by analyzing the principle of vocalization theory, emotion models based on Gaussian mixture model are generated and the similarity of their templates is obtained. A series of experiments is performed with recorded speech based on Gaussian mixture model and indicates the system gains high performance and better robustness.


2015 ◽  
Vol 51 (1) ◽  
pp. 112-114 ◽  
Author(s):  
Peng Song ◽  
Yun Jin ◽  
Cheng Zha ◽  
Li Zhao

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