TuneAura: Music Recommendation System using Facial Expressions

Music plays an integral role in daily life, serving as a universal medium for mood enhancement and emotional expression. Traditional methods of music selection rely on manual input, which can be cumbersome and inefficient. In response, we introduce a novel approach leveraging facial emotion recognition to automatically curate personalized music playlists tailored to the user's emotional state.

This paper presents an automated music selection based on real-time facial expression analysis. By harnessing the emotive power of music, we propose a system that captures users' emotions through facial cues and generates personalized playlists to complement their mood. Our system offers efficient music recommendations, enhancing user experience across various activities. This approach aims to revolutionize music consumption by seamlessly aligning auditory stimuli with emotional states, fostering a more immersive and enriching listening experience.