MoodTune

Developed a web application that recommends K-Pop playlists based on the user’s input emotion or mood. Users can enter how they feel (e.g., happy, sad, stressed, excited), and the system analyzes the input to generate a personalized playlist that matches the emotional context. In addition to playlist recommendations, the platform provides a mood tracking feature that allows users to record and visualize their emotional patterns over time. This helps users understand their mood trends while discovering music that aligns with their feelings. Key Features: • Emotion-based K-Pop playlist recommendation • Natural language input for mood detection • Personalized music suggestions • Mood tracking and visualization • User-friendly web interface This project focuses on enhancing user experience by combining music recommendation logic with emotional data tracking, creating a more personalized and engaging listening experience.