Color-based music playlist generator: A personalized approach

This project presents an innovative music playlist generator designed to align with the user’s emotional state. The system utilizes a real-time emotion input mechanism to curate personalized playlists that reflect the user’s current mood. By integrating a simple user interface with efficient data management and the Fisher-Yates shuffle algorithm, the generator provides a dynamic and engaging music selection experience. Users can select their emotional state via a range slider, which triggers the system to fetch and shuffle a playlist of music tracks from a pre-defined JSON database. The approach enhances traditional music recommendation methods by adding an environmental context, resulting in a more relevant and satisfying listening experience. The system’s modular design allows for future enhancements, such as incorporating advanced recommendation algorithms and expanding its functionality. Overall, this project demonstrates the potential of color-driven recommendations to improve user engagement and satisfaction in music selection.