A real-time recognition model of teachers' voice and emotion for college online education

In order to improve the recognition rate of teachers' voice emotion recognition, this paper proposes a new model of teachers' voice emotion recognition for online education in colleges and universities. In the process of online education, there are some errors and noises in Teachers' voice, which need to be corrected and denoised. On this basis, teachers' voice emotion features are selected for dimensionality reduction, based on the reduced teachers' voice emotion feature parameters. The template of teacher's speech emotion recognition is constructed to realize the real-time recognition of teacher's speech emotion. The experimental results show that, under different experimental objects, the accuracy of the proposed model is much higher than that of the contrast model, which proves that the proposed model has good performance of emotion recognition.