Music Recommendation System Based on Face Emotion Recognition

This research paper presents a novel music recommendation system that leverages face emotion recognition to suggest songs that match the user's emotional state. The system uses computer vision techniques to analyze facial expressions and detect emotions such as happiness, sadness, anger, or surprise in real-time. Based on the recognized emotion, the system dynamically recommends music tracks that align with the user's current mood. The main goal of this system is to enhance user experience by providing emotionally relevant music, making the listening process more personalized and satisfying. This paper discusses the architecture, algorithms, and datasets used, as well as the potential applications and limitations of emotion-based music recommendation systems.