A Novel Approach of Emotion Recognition based on Selective Ensemble

被引：0

作者：

Zhu, Zhenguo ^{[1
]}

He, Kun ^{[2
]}

机构：

[1] Chongqing Jiaotong Univ, Sch Comp & Informat, Chongqing 400074, Peoples R China

[2] Chongqing Univ Posts & Telecommun, Inst Comp Sci & Technol, Chongqing 400065, Peoples R China

来源：

2008 3RD INTERNATIONAL CONFERENCE ON INTELLIGENT SYSTEM AND KNOWLEDGE ENGINEERING, VOLS 1 AND 2 | 2008年

关键词：

Affective computing; emotion recognition; support vector machine; ensemble learning; selective ensemble;

D O I：

10.1109/ISKE.2008.4731019

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Emotion recognition is an important module in affective computing. It is usually studied based on facial and audio information with methodologies such as ANN, fuzzy set, SVM, HMM, etc. In this paper, a novel approach based on selective ensemble is proposed for emotion recognition. Simulation experiments prove that the proposed method has better performance than the method of single classifier, even better than bagging. In the end, further research works is discussed.

引用

页码：695 / +

页数：2

共 50 条

[41] Expression Detection Based on a Novel Emotion Recognition Method
Gong, Xun
Yang, Yong
Lin, Jianhui
Li, Tianrui
INTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMS, 2011, 4 (01) : 44 - 53
[42] Neural network-based blended ensemble learning for speech emotion recognition
Yalamanchili, Bhanusree
Samayamantula, Srinivas Kumar
Anne, Koteswara Rao
MULTIDIMENSIONAL SYSTEMS AND SIGNAL PROCESSING, 2022, 33 (04) : 1323 - 1348
[43] Expression Detection Based on a Novel Emotion Recognition Method
Xun Gong
Yong Yang
Jianhui Lin
Tianrui Li
International Journal of Computational Intelligence Systems, 2011, 4 (1) : 44 - 53
[44] SPEAKER VARIABILITY IN EMOTION RECOGNITION - AN ADAPTATION BASED APPROACH
Ding, Ni
Sethu, Vidhyasaharan
Epps, Julien
Ambikairajah, Eliathamby
2012 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), 2012, : 5101 - 5104
[45] Efficient approach for EEG-based emotion recognition
Senguer, D.
Siuly, S.
ELECTRONICS LETTERS, 2020, 56 (25) : 1361 - 1364
[46] A DCRNN-based ensemble classifier for speech emotion recognition in Odia language
Swain, Monorama
Maji, Bubai
Kabisatpathy, P.
Routray, Aurobinda
COMPLEX & INTELLIGENT SYSTEMS, 2022, 8 (05) : 4237 - 4249
[47] Exploiting a Vowel Based Approach for Acted Emotion Recognition
Ringeval, Fabien
Chetouani, Mohamed
VERBAL AND NONVERBAL FEATURES OF HUMAN-HUMAN AND HUMAN-MACHINE INTERACTIONS, 2008, 5042 : 243 - 254
[48] Audio Segmentation based Approach for Improved Emotion Recognition
Pandharipande, Meghna Abhishek
Kopparapu, Sunil Kumar
TENCON 2015 - 2015 IEEE REGION 10 CONFERENCE, 2015,
[49] A novel dynamic rough subspace based selective ensemble
Guo, Yuwei
Jiao, Licheng
Wang, Shuang
Wang, Shuo
Liu, Fang
Rong, Kaixuan
Xiong, Tao
PATTERN RECOGNITION, 2015, 48 (05) : 1638 - 1652
[50] A selective ensemble learning approach based on evolutionary algorithm
Zhang, Yong
Liu, Bo
Yu, Jiaxin
JOURNAL OF INTELLIGENT & FUZZY SYSTEMS, 2017, 32 (03) : 2365 - 2373

← 1 2 3 4 5 →