STUDY ON MUSIC RECOMMENDATION USING USER'S FACE EMOTION USING PYTHON PROGRAMMING AND MACHINE LEARNING

Music has a profound influence on human emotions and behavior. This paper presents a novel music recommendation system that leverages facial emotion recognition to curate personalized playlists. The system dynamically selects music that aligns with the user's emotional state by utilizing Convolutional Neural Networks (CNN) for real-time facial expression analysis. Unlike conventional recommendation systems that depend on historical user preferences, the proposed model provides an intuitive, real-time solution for emotion-based music suggestions. The results show a significant improvement in user experience and engagement.