Emotion Detection in E-learning Using Expectation-Maximization Deep Spatial-Temporal Inference Network

Abstract

It is very useful for the E-learning systems to detect the students emotional state accurately, and this can remind the teacher in time to change the teaching rhythm or content to meet the student’s emotional changes for making the teaching effect optimization. In this paper, we propose an emotion detection method based on a deep learning approach, Expectation-maximization Deep Spatial-Temporal Inference Network (EM-DeSTIN). This method takes the student’s facial expression as input and combine with Support Vector Machine (SVM) to implement emotion classification and identification. Experimental results show that the proposed method improves the performance of detecting emotion in a noisy environment compared with other methods.