Speech Emotion Recognition Based on Joint Self-Assessment Manikins and Emotion Labels

被引：5
|
作者：
Chen, Jing-Ming [1 ]
Chang, Pao-Chi [1 ]
Liang, Kai-Wen [1 ]
机构：
[1] Natl Cent Univ, Dept Commun Engn, Taoyuan, Taiwan
来源：
2019 IEEE INTERNATIONAL SYMPOSIUM ON MULTIMEDIA (ISM 2019) | 2019年
关键词：
Speech emotion recognition; Self-Assessment Manikin; Deep learning; Convolutional recurrent neural network;
D O I：
10.1109/ISM46123.2019.00073
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
In this work, we propose a system for speech emotion recognition based on regression models and classification models jointly. This speech emotion recognition technology can achieve the accuracy of 64.70% in the dataset of script and improvised mixed scenes. The accuracy can be up to 66.34% in the dataset with only improvised scenes. Compared to the state-of-art technology without the mental states, the accuracy of the proposed method is increased by 2.95% and 2.09% respect to improvised and mixed scenes. The results show that the characteristics of mental states can effectively improve the performance of speech emotion recognition.
引用
收藏
页码：327 / 330
页数：4
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