The influence of music teaching appreciation on the mental health of college students based on multimedia data analysis

The mental health problem of college students has gradually become the focus of people’s attention. The music appreciation course in university is a very effective approach of psychological counseling, and it is urgent to explore the role of music appreciation in psychological adjustment. Therefore, we propose an emotion classification model based on particle swarm optimization (PSO) to study the effect of inter active music appreciation teaching on the mental health of college students. We first extract musical features as input. Then, the extracted music appreciation features generate subtitles of music information. Finally, we weight the above features, input them into the network, modify the network through particle swarm optimization, and output the emotional class of music. The experimental results show that the music emotion classification model has a high classification accuracy of 82.6%, and can obtain the emotional categories included in interactive music appreciation, which is helpful to guide the mental health of college students in music appreciation teaching.