EmoTune.AI is an innovative, AI-powered web application built with Streamlit that creates a personalized, mood-responsive audio experience. It detects users' emotions through multiple inputs—facial emotion analysis (via image uploads), voice tone analysis, text descriptions, and biometric data (e.g., heart rate, SpO2, motion)—and generates tailored music to match or uplift their mood. The app features a visually stunning interface with gradient backgrounds, particle effects, and animated elements, enhancing user engagement
- Multi-Modal Mood Detection: Detects emotions via facial recognition (image uploads), voice tone (audio uploads), text input, and biometric data (heart rate, SpO2, motion).
- AI-Generated Music: Creates custom music tracks tailored to the user’s mood, with uplifting tracks for negative emotions.
- Personalized Recommendations: Suggests YouTube songs, Spotify tracks, and movies based on mood, respecting user genre preferences.
- Gamification: Awards badges like "Mood Explorer" (5 analyses) and "Streak Master" (3 consecutive same moods).
- Emotional Support Chatbot: Provides a sidebar chatbot for emotional support.
- Biometric Insights: Displays insights from biometric data (e.g., high heart rate detection).
- Mood History & Trends: Tracks and visualizes mood trends with a graph.
- Global Impact: Offers location-based mental health resources using IP geolocation.
- Privacy & Ethics: Ensures data privacy with local processing and a privacy dashboard.
- Voice Control: Supports hands-free operation via voice commands.
- Emotional Memory Capsules: Saves mood-based moments with music for reflection.
- Holistic Mood Detection: Combines facial, voice, text, and biometric inputs for a comprehensive emotional analysis, unlike most apps that rely on a single input.
- Mood-Responsive Music Generation: Generates custom music to match or uplift the user’s mood, a feature not commonly found in standard music apps.
- Gamified Emotional Wellness: Integrates gamification (badges, streaks) to make emotional well-being engaging and rewarding.
- Voice Cloning Model: Voice cloning model to personalize AI-generated music by mimicking the user’s voice, creating a unique and emotionally resonant audio experience.
- Real-Time Webcam Analysis: Add live webcam-based facial emotion detection for continuous mood monitoring.
- Advanced Music Generation: Use deep learning (e.g., Magenta) for more complex, genre-specific music tracks.
- Multilingual Support: Support multiple languages for global accessibility.
- AR/VR Integration: Create immersive 3D mood visualizations with music.
- Mobile App: Develop iOS and Android apps for broader reach.
- Input: Users select their mood or provide inputs (image, audio, text, biometrics).
- Mood Detection: AI analyzes inputs to detect the mood (e.g., happy, sad) with a confidence score.
- Music & Recommendations: Generates custom music and suggests songs, movies, and Spotify tracks based on mood.
- Engagement: Offers gamification, a chatbot, mood history, and memory capsules for interaction.
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Mental Health Support: Promotes emotional well-being by providing music therapy and mental health resources, reducing stress (music can reduce stress by up to 65%, per WHO).
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Community Building: Encourages users to share uplifting music, fostering a supportive community.
For queries or collaborations, reach out at [[email protected]] or visit my GitHub repository.