Speech Emotion Recognition Based on Speech Segment Using LSTM with Attention Model

被引：0
|
作者：
Atmaja, Bagus Tris [1 ,2 ]
Akagi, Masato [3 ]
机构：
[1] Japan Adv Inst Sci & Tech, Nomi, Japan
[2] Inst Teknol Sepuluh Nopember, Surabaya, Indonesia
[3] Japan Adv Inst Sci & Tech JAIST, Sch Informat Sci, Nomi, Japan
来源：
2019 IEEE INTERNATIONAL CONFERENCE ON SIGNALS AND SYSTEMS (ICSIGSYS) | 2019年
关键词：
voice segments; silence removal; speech emotion recognition; attention model;
D O I：
10.1109/icsigsys.2019.8811080
中图分类号：
TP [自动化技术、计算机技术];
学科分类号：
0812 ;
摘要：
Automatic speech emotion recognition has become popular as it enables natural interaction between human-machine interaction. One modality of recognizing emotion is speech. However, the speech also contains silence that may not relevant to emotion. Two ways to improve performance is by removing silence and/or paying more attention to speech segment while ignoring the silence. In this paper, we propose both, a combination of silence removal and attention model to improve speech emotion recognition performance. The results show that utilizing combination silence removal and attention model outperforms the use of either noise removal only or attention model only.
引用
收藏
页码：40 / 44
页数：5
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