TY - GEN
T1 - Using facial expression to detect emotion in e-learning system
T2 - 2nd International Symposium on Emerging Technologies for Education, SETE 2017, held in Conjunction with the 16th International Conference on Web-based learning, ICWL 2017
AU - Sun, Ai
AU - Li, Ying Jian
AU - Huang, Yueh Min
AU - Li, Qiong
N1 - Publisher Copyright:
© Springer International Publishing AG 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - https://www.scopus.com/pages/publications/85041435041
UR - https://www.scopus.com/pages/publications/85041435041#tab=citedBy
U2 - 10.1007/978-3-319-71084-6_52
DO - 10.1007/978-3-319-71084-6_52
M3 - Conference contribution
AN - SCOPUS:85041435041
SN - 9783319710839
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 446
EP - 455
BT - Emerging Technologies for Education - 2nd International Symposium, SETE 2017, Held in Conjunction with ICWL 2017, Revised Selected Papers
A2 - Huang, Tien-Chi
A2 - Lau, Rynson
A2 - Huang, Yueh-Min
A2 - Spaniol, Marc
A2 - Yuen, Chun-Hung
PB - Springer Verlag
Y2 - 20 September 2017 through 22 September 2017
ER -