Music Recommendation System Based on Real-Time Emotion Analysis

As more and more people like listening to music, the relationship between music and people’s emotional expression becomes closer and closer, and the music recommendation platform can help those who love music to screen out the parts that can meet people’s psychological demands from a large number of music works. Traditional music recommendation platforms often only rely on the simple classification of music works and the processing of music information listened to by users in history, but they can not adjust the recommended music categories according to the changes of users’ real-time emotional state to meet the changing needs of users. To meet this demand, this paper aims to design a music recommendation system based on real-time emotional analysis, so that the audience can get a more satisfactory user experience.