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
相关论文
共 50 条
  • [1] Attention-Based Dense LSTM for Speech Emotion Recognition
    Xie, Yue
    Liang, Ruiyu
    Liang, Zhenlin
    Zhao, Li
    IEICE TRANSACTIONS ON INFORMATION AND SYSTEMS, 2019, E102D (07): : 1426 - 1429
  • [2] Siamese Attention-Based LSTM for Speech Emotion Recognition
    Nizamidin, Tashpolat
    Zhao, Li
    Liang, Ruiyu
    Xie, Yue
    Hamdulla, Askar
    IEICE TRANSACTIONS ON FUNDAMENTALS OF ELECTRONICS COMMUNICATIONS AND COMPUTER SCIENCES, 2020, E103A (07) : 937 - 941
  • [3] Speech Emotion Recognition Based on Acoustic Segment Model
    Zheng, Siyuan
    Du, Jun
    Zhou, Hengshun
    Bai, Xue
    Lee, Chin-Hui
    Li, Shipeng
    2021 12TH INTERNATIONAL SYMPOSIUM ON CHINESE SPOKEN LANGUAGE PROCESSING (ISCSLP), 2021,
  • [4] A Robust Framework for Speech Emotion Recognition Using Attention Based Convolutional Peephole LSTM
    Paramasivam, Ramya
    Lavanya, K.
    Divakarachari, Parameshachari Bidare
    Camacho, David
    INTERNATIONAL JOURNAL OF INTERACTIVE MULTIMEDIA AND ARTIFICIAL INTELLIGENCE, 2025,
  • [5] Empirical Interpretation of Speech Emotion Perception with Attention Based Model for Speech Emotion Recognition
    Jalal, Md Asif
    Milner, Rosanna
    Hain, Thomas
    INTERSPEECH 2020, 2020, : 4113 - 4117
  • [6] Speech Emotion Classification Using Attention-Based LSTM
    Xie, Yue
    Liang, Ruiyu
    Liang, Zhenlin
    Huang, Chengwei
    Zou, Cairong
    Schuller, Bjoern
    IEEE-ACM TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2019, 27 (11) : 1675 - 1685
  • [7] Attention-LSTM-Attention Model for Speech Emotion Recognition and Analysis of IEMOCAP Database
    Yu, Yeonguk
    Kim, Yoon-Joong
    ELECTRONICS, 2020, 9 (05)
  • [8] Hybrid LSTM-Attention and CNN Model for Enhanced Speech Emotion Recognition
    Makhmudov, Fazliddin
    Kutlimuratov, Alpamis
    Cho, Young-Im
    APPLIED SCIENCES-BASEL, 2024, 14 (23):
  • [9] Attention guided 3D CNN-LSTM model for accurate speech based emotion recognition
    Atila, Orhan
    Sengur, Abdulkadir
    APPLIED ACOUSTICS, 2021, 182
  • [10] Speech Emotion Recognition using MFCC features and LSTM network
    Kumbhar, Harshawardhan S.
    Bhandari, Sheetal U.
    2019 5TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION, CONTROL AND AUTOMATION (ICCUBEA), 2019,
12345