MusFinder is an intelligent music recommendation system designed to integrate with
existing music applications, enhancing users' listening experience by providing more
personalized and context-aware music suggestions.
Low-Fidelity and Working Prototype
Demo Video
Highlights of Evaluation Result
Integrated a Large Language Model (LLM) API and built a user-friendly interface compatible with existing regular music applications.
Photo/Keyword Input: 100% task success; Users found it intuitive and matched to mood.
Context-Aware Recommendations: 80% saw appropriate music adjustments based on location.
Real-Time Feedback: 80% reported better recommendations after feedback input.
User Feedback: Praised interface ease and music match quality; suggested faster feedback response.
Behavioral Observations: Users explored freely with minimal guidance; slight hesitation with image uploads.
