Applying articulatory features to speech emotion recognition

被引:7
|
作者
Zhou, Yu [1 ]
Sun, Yanqing [1 ]
Yang, Lin [1 ]
Yan, Yonghong [1 ]
机构
[1] Chinese Acad Sci, Inst Acoust, ThinkIT Speech Lab, Beijing, Peoples R China
来源
2009 INTERNATIONAL CONFERENCE ON RESEARCH CHALLENGES IN COMPUTER SCIENCE, ICRCCS 2009 | 2009年
关键词
articulatory feature; emotion recognition;
D O I
10.1109/ICRCCS.2009.26
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
In this paper, we present an approach that using articulatory features (AFs) derived from spectral features for speech emotion recognition. Also, we investigated the combination of AFs and spectral features. Systems based on AFs only and combined spectral-articulatory features are tested on the CASIA Mandarin emotional corpus. Experiments results show that AFs alone are not suitable for speech emotion recognition and that the combination of spectral features and AFs don't improve the performance of the system that using only spectral features.
引用
收藏
页码:73 / 76
页数:4
相关论文
共 50 条
  • [1] Articulatory Features for "Meeting" Speech Recognition
    Metze, Florian
    INTERSPEECH 2006 AND 9TH INTERNATIONAL CONFERENCE ON SPOKEN LANGUAGE PROCESSING, VOLS 1-5, 2006, : 581 - 584
  • [2] Speech recognition using cepstral articulatory features
    Najnin, Shamima
    Banerjee, Bonny
    SPEECH COMMUNICATION, 2019, 107 : 26 - 37
  • [3] Determining Optimal Features for Emotion Recognition from Speech by applying an Evolutionary Algorithm
    Huebner, David
    Vlasenko, Bogdan
    Grosser, Tobias
    Wendemuth, Andreas
    11TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION 2010 (INTERSPEECH 2010), VOLS 3 AND 4, 2010, : 2358 - 2361
  • [4] Robust Speech Recognition Combining Cepstral and Articulatory Features
    Zha, Zhuan-ling
    Hu, Jin
    Zhan, Qing-ran
    Shan, Ya-hui
    Xie, Xiang
    Wang, Jing
    Cheng, Hao-bo
    PROCEEDINGS OF 2017 3RD IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND COMMUNICATIONS (ICCC), 2017, : 1401 - 1405
  • [5] Whispery speech recognition using adapted articulatory features
    Jou, SC
    Schultz, T
    Waibel, A
    2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING, 2005, : 1009 - 1012
  • [6] Articulatory and Stacked Bottleneck Features for Low Resource Speech Recognition
    Shetty, Vishwas M.
    Sharon, Rini A.
    Abraham, Basil
    Seeram, Tejaswi
    Prakash, Anusha
    Ravi, Nithya
    Umesh, S.
    19TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2018), VOLS 1-6: SPEECH RESEARCH FOR EMERGING MARKETS IN MULTILINGUAL SOCIETIES, 2018, : 3202 - 3206
  • [7] Speech recognition based on a combination of acoustic features with articulatory information
    LU Xugang DANG Jianwu (Japan Advanced Institute of Science and Technology
    ChineseJournalofAcoustics, 2005, (03) : 271 - 279
  • [8] A STUDY ON ROBUSTNESS OF ARTICULATORY FEATURES FOR AUTOMATIC SPEECH RECOGNITION OF NEUTRAL AND WHISPERED SPEECH
    Srinivasan, Gokul
    Illa, Aravind
    Ghosh, Prasanta Kumar
    2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2019, : 5936 - 5940
  • [9] Applying Machine Learning Techniques for Speech Emotion Recognition
    Tarunika, K.
    Pradeeba, R. B.
    Aruna, P.
    2018 9TH INTERNATIONAL CONFERENCE ON COMPUTING, COMMUNICATION AND NETWORKING TECHNOLOGIES (ICCCNT), 2018,
  • [10] Integrating Language and Emotion Features for Multilingual Speech Emotion Recognition
    Heracleous, Panikos
    Mohammad, Yasser
    Yoneyama, Akio
    HUMAN-COMPUTER INTERACTION. MULTIMODAL AND NATURAL INTERACTION, HCI 2020, PT II, 2020, 12182 : 187 - 196