Ideological and political empowering English teaching: ideological education based on artificial intelligence in classroom emotion recognition

This is the authors' abstract. We don't add key points for this paper.

Emotions play an important role in human decision-making, interaction and cognition. Accurately identifying human emotions can provide effective support for human decision-making and solutions. Reflecting the learning situation with classroom emotions can assist teachers in implementing teaching interventions, so as to help teachers carry out accurate teaching. In this paper, we propose a classroom emotion recognition method based on multi-modal fusion of speech and text. We first adopt the CNN and LSTM to extract the spatio-temporal feature from the speech data. Then, we adopt a LSTM model to perform feature extraction on text data. After obtaining these two types of features, we finally design a fusion model based on attention mechanism. The experimental results prove that the method proposed in this paper has good prediction performance, which is of great significance for the classroom emotion recognition.