Emotional recognition and feedback of students in English e-learning based on computer vision and face recognition algorithms

Abstract

In existing English teaching, teachers often find it difficult to accurately understand students’ emotional changes, thus unable to adjust teaching strategies in a timely manner. Therefore, the introduction of computer vision and facial recognition algorithms will help improve the effectiveness of English teaching. This article is based on computer vision technology and facial recognition algorithms. Based on the sample data provided during the learning process, a model is learned and established to recognize facial expressions under different emotions and identify students’ emotional states. Use computer vision technology to capture and analyze students’ facial expressions in real-time. Then, facial recognition algorithms are used to recognize and classify the captured facial features to determine the current emotional state of the students. Finally, based on the students’ emotional state, the system will provide corresponding feedback. This technology based on computer vision and facial recognition algorithms can help teachers better understand students’ emotional changes, adjust teaching strategies in a timely manner, provide personalized learning feedback, and thereby improve students’ learning effectiveness and the quality of English teaching. This technology can also provide students with a better learning experience, enhancing their learning motivation and interest.