A survey of emotion recognition methods with emphasis on E-Learning environments

Abstract

Emotions play an important role in the learning process. Considering the learner's emotions is essential for electronic learning (e-learning) systems. Some researchers have proposed that system should induce and conduct the learner's emotions to the suitable state. But, at first, the learner's emotions have to be recognized by the system. There are different methods in the context of human emotions recognition. The emotions can be recognized by asking from the user, tracking implicit parameters, voice recognition, facial expression recognition, vital signals and gesture recognition. Moreover, hybrid methods have been also proposed which use two or more of these methods through fusing multi-modal emotional cues. In the e-learning systems, the system's user is the learner. For some reasons, which have been discussed in this study, some of the user emotions recognition methods are more suitable in the e-learning systems and some of them are inappropriate. In this work, different emotion theories are reviewed. Then, various emotions recognition methods have been represented and their advantages and disadvantages of them have been discussed for utilizing in the e-learning systems. According to the findings of this research, the multi-modal emotion recognition systems through information fusion as facial expressions, body gestures and user's messages provide better efficiency than the single-modal ones.