Combining spectral and prosodic information for emotion recognition in the Interspeech 2009 Emotion Challenge

被引:0
|
作者
Luengo, Iker [1 ]
Navas, Eva [1 ]
Hernaez, Inmaculada [1 ]
机构
[1] Univ Basque Country, Dept Elect & Telecommun, Madrid, Spain
关键词
expressive speech; emotion; feature selection; DETECTION ALGORITHMS; SPEECH;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
This paper describes the system presented at the Interspecch 2009 Emotion Challenge. It relies on both spectral and prosodic features in order to automatically detect the emotional state of the speaker. As both kinds of features have very different characteristics, they are treated separately, creating two sub-classifiers, one using the spectral features and the other one using the prosodic ones. The results of these two classifiers are then combined with a fusion system based on Support Vector Machines.
引用
收藏
页码:332 / 335
页数:4
相关论文
共 50 条
  • [21] Emotion Recognition In The Wild Challenge 2013
    Dhall, Abhinav
    Goecke, Roland
    Joshi, Jyoti
    Wagner, Michael
    Gedeon, Tom
    [J]. ICMI'13: PROCEEDINGS OF THE 2013 ACM INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 2013, : 509 - 515
  • [22] Emotion Recognition in the Wild Challenge 2016
    Dhall, Abhinav
    Goecke, Roland
    Joshi, Jyoti
    Gedeon, Tom
    [J]. ICMI'16: PROCEEDINGS OF THE 18TH ACM INTERNATIONAL CONFERENCE ON MULTIMODAL INTERACTION, 2016, : 587 - 588
  • [23] The University of Passau Open Emotion Recognition System for the Multimodal Emotion Challenge
    Deng, Jun
    Cummins, Nicholas
    Han, Jing
    Xu, Xinzhou
    Ren, Zhao
    Pandit, Vedhas
    Zhang, Zixing
    Schuller, Bjoern
    [J]. PATTERN RECOGNITION (CCPR 2016), PT II, 2016, 663 : 652 - 666
  • [24] Speech emotion classification using combined neurogram and INTERSPEECH 2010 paralinguistic challenge features
    Jassim, Wissam A.
    Paramesran, Raveendran
    Harte, Naomi
    [J]. IET SIGNAL PROCESSING, 2017, 11 (05) : 587 - 595
  • [25] GMM based Speaker Variability Compensated System for Interspeech 2013 ComParE Emotion Challenge
    Sethu, Vidhyasaharan
    Epps, Julien
    Ambikairajah, Eliathamby
    Li, Haizhou
    [J]. 14TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION (INTERSPEECH 2013), VOLS 1-5, 2013, : 205 - 209
  • [26] Multimodal Emotion Recognition Based on the Decoupling of Emotion and Speaker Information
    Gajsek, Rok
    Struc, Vitomir
    Mihelic, France
    [J]. TEXT, SPEECH AND DIALOGUE, 2010, 6231 : 275 - 282
  • [27] Automatic Emotion Recognition using Auditory and Prosodic Indicative Features
    Gharsellaoui, Soumaya
    Selouani, Sid-Ahmed
    Dahmane, Adel Omar
    [J]. 2015 IEEE 28TH CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING (CCECE), 2015, : 1265 - 1270
  • [28] Emotion Recognition from Speech using Prosodic and Linguistic Features
    Pervaiz, Mahwish
    Khan, Tamim Ahmed
    [J]. INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2016, 7 (08) : 84 - 90
  • [29] Utterance and Syllable Level Prosodic Features for Automatic Emotion Recognition
    Ben Alex, Starlet
    Babu, Ben P.
    Mary, Leena
    [J]. 2018 IEEE RECENT ADVANCES IN INTELLIGENT COMPUTATIONAL SYSTEMS (RAICS), 2018, : 31 - 35
  • [30] Prosodic feature normalization for emotion recognition by using synthesized speech
    Suzuki, Motoyuki
    Nakagawa, Shohei
    Kita, Kenji
    [J]. ADVANCES IN KNOWLEDGE-BASED AND INTELLIGENT INFORMATION AND ENGINEERING SYSTEMS, 2012, 243 : 306 - 313