A Deep Learning Approach for Online Learning Emotion Recognition

In recent years, online teaching has developed rapidly with numerous online-education platforms and diversified online-education models. Compared with traditional classroom teaching, online teaching has advantages, such as not being constrained by place and offering a wide range of interactions. Simultaneously, online teaching lacks interaction between lecturers and learners, and the lecturers are unable to observe the learners face to face. This paper proposes and implements a real-time emotion-score recognition model based on the convolutional neural network. It captures the learners' learning picture through a webcam, judges the learners' learning emotions in real time, and provides feedback to the lecturer, achieving real-time feedback of emotion in distance education. The model helps to enhance the interaction between the lecturer and learner, and it helps personalize education.