Emotion-Based Music Recommendation System

Abstract

Music is the form of art known to have a greater connection with a person's emotion. It has got a unique ability to lift up one's mood. If a user receives a recommendation based on his preference, it will also improve his listing experience. Music recommendations have existed for a long time. Still, in most scenarios, the recommendation is decided after learning the user preferences over time, like looking at their past song preferences, the amount of time they listen to the music, etc. This paper suggests a neural network-based approach to song recommendation where their facial expressions detect a person's mood. This approach is more efficient than the existing ones and eases users' work of first searching and creating a specific playlist. Facial expressions play a crucial role in detecting a person's mood. A webcam or camera is used to picture a face, and input is extracted from that picture. This input is also used for determining an individual's mood.