Using Facial Expression to Detect Emotion in E-learning System: A Deep Learning Method

被引:15
作者
Sun, Ai [1 ]
Li, Ying-Jian [2 ]
Huang, Yueh-Min [1 ]
Li, Qiong [2 ]
机构
[1] Natl Cheng Kung Univ, Dept Engn Sci, Tainan, Taiwan
[2] Harbin Inst Technol, Sch Comp Sci & Technol, Harbin, Heilongjiang, Peoples R China
来源
EMERGING TECHNOLOGIES FOR EDUCATION | 2018年 / 10676卷
关键词
E-learning; Emotion detection; Facial expression; Deep learning; RECOGNITION;
D O I
10.1007/978-3-319-71084-6_52
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
E-learning system is becoming more and more popular among students nowadays. However, the emotion of students is usually neglected in e-learning system. This study is mainly concerned about using facial expression to detect emotion in e-learning system. A deep learning method called convolutional neural network (CNN) is used in our research. Firstly, CNN is introduced to detect emotion in e-learning system based on using facial expression in this paper. Secondly, the training process and testing process of CNN are described. To learn about the accuracy of CNN in emotion detection, three databases (CK+, JAFFE and NVIE) are chosen to train and test the model. 10-fold cross validation method is used to calculate the accuracy. Thirdly, we introduce how to apply the trained CNN to e-learning system, and the design of e-learning system with emotion detection module is given. At last, we propose the design of an experiment to evaluate the performance of this method in real e-learning system.
引用
收藏
页码:446 / 455
页数:10
相关论文
共 29 条
[1]  
[Anonymous], 2003, Journal of Asynchronous Learning Networks
[2]  
[Anonymous], 2010, P 3 INT WORKSH EMOTI
[3]  
[Anonymous], 2015, Journal of Computational and Graphical Statistics
[4]  
[Anonymous], 2015, 2015 21 KOR JAP JOIN
[5]   An E-learning System With Multifacial Emotion Recognition Using Supervised Machine Learning [J].
Ashwin, T. S. ;
Jose, Jijo ;
Raghu, G. ;
Reddy, G. Ram Mohana .
2015 IEEE SEVENTH INTERNATIONAL CONFERENCE ON TECHNOLOGY FOR EDUCATION (T4E), 2015, :23-26
[6]  
Brodny G, 2016, C HUM SYST INTERACT, P397, DOI 10.1109/HSI.2016.7529664
[7]   Sentiment analysis in financial texts [J].
Chan, Samuel W. K. ;
Chong, Mickey W. C. .
DECISION SUPPORT SYSTEMS, 2017, 94 :53-64
[8]   Context-Dependent Pre-Trained Deep Neural Networks for Large-Vocabulary Speech Recognition [J].
Dahl, George E. ;
Yu, Dong ;
Deng, Li ;
Acero, Alex .
IEEE TRANSACTIONS ON AUDIO SPEECH AND LANGUAGE PROCESSING, 2012, 20 (01) :30-42
[9]  
Devlin J, 2014, PROCEEDINGS OF THE 52ND ANNUAL MEETING OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS, VOL 1, P1370
[10]   FACIAL EXPRESSIONS OF EMOTION - AN OLD CONTROVERSY AND NEW FINDINGS [J].
EKMAN, P .
PHILOSOPHICAL TRANSACTIONS OF THE ROYAL SOCIETY OF LONDON SERIES B-BIOLOGICAL SCIENCES, 1992, 335 (1273) :63-69