Multimedia English teaching analysis based on deep learning speech enhancement algorithm and robust expression positioning

Abstract

In multimedia English teaching, learners face such an indifferent computer screen without emotion and feel the fun of interaction and emotional stimulation, which will cause resentment and affect the learner’s learning effect. In order to improve the efficiency of multimedia English teaching, aiming at the lack of emotion in multimedia English education, this study proposes an intelligent network teaching system model based on deep learning speech enhancement and facial expression recognition. Moreover, this study uses emotional calculation as the theoretical basis and uses facial expression recognition as the core technology to judge and understand the emotional state by capturing and recognizing the facial expressions of online learners. In addition, this study has carried out experimental tests on the effect of the identification method of this paper and verified that the method has good detection effect on the real smile micro-expressions through two sets of experiments and can provide theoretical reference for subsequent related research.