Music Recommendation System based on Facial Expression

Abstract

Music streaming services now make it simple to listen to a wide variety of music. Consumers are increasingly relying on recommendation systems to help them choose appropriate music at all times. However, there is certain chances for improvement in terms of customization and emotion-based suggestions. Furthermore, music tastes will change depending on the user’s current mood. If these issues are not solved, these online services will fail to meet user expectations. This research study shows how to create a personalized music recommendation system based on listener thoughts, emotions, and facial expressions. A recommendation system is created using a combination of artificial intelligence technology and generalized music therapy approaches to help people choose music for different life situations while maintaining their mental and physical health.