🎧 Emotion-Based Music Recommender

An AI-powered web application that detects user mood via text or voice input and recommends personalized songs using Spotify, YouTube, and lyrics analysis.

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🎬 Demo

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🔍 Overview

This project intelligently recommends music based on a user's emotional state. It leverages:

• Gemini AI for emotion detection (text/voice)
• Spotify and YouTube APIs for music discovery
• Genius/Gemini fallback for lyrics analysis
• Librosa for audio feature extraction
• SQLite for lightweight local storage

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🚀 Features

• 🎤 Dual-mode mood input (Text + Voice)
• 🤖 Gemini-powered mood analysis
• 🎶 Real-time music suggestions
• 🧠 Fallback lyrics + mood extraction via Gemini
• 📊 Tempo & key analysis with Librosa
• 💾 Database storage using SQLite

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🛠️ Tech Stack

Category	Tools/APIs
Language	Python 3.x
Backend	Flask
AI/ML	Google Gemini, Librosa
APIs	Spotify, YouTube Data API, Genius
Frontend	HTML5, CSS3, JavaScript (Basic)
Database	SQLite

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⚙️ Setup Instructions

🔐 1. Clone the Repository

git clone https://github.com/sumannaidur/Emotion-Based-Music-Recommender.git
cd Emotion-Based-Music-Recommender

🧪 2. Create a Virtual Environment

python -m venv venv
source venv/bin/activate    # On Windows: venv\Scripts\activate

📦 3. Install Dependencies

pip install -r requirements.txt

🔑 4. Set Up API Keys

Create a .env file in the root directory with the following variables:

SPOTIFY_CLIENT_ID=your_spotify_client_id
SPOTIFY_CLIENT_SECRET=your_spotify_client_secret
YOUTUBE_API_KEY=your_youtube_api_key
GEMINI_API_KEY_1=your_gemini_key
GEMINI_API_KEY_2=optional_secondary
GEMINI_API_KEY_3=optional_tertiary

Note: Use dotenv to securely load environment variables.

▶️ 5. Run the App

python app.py

Visit: http://localhost:5000

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🎯 How It Works

1. Mood Detection: User inputs mood via text or voice
2. AI Analysis: Gemini AI processes and categorizes emotions
3. Music Matching: System searches Spotify/YouTube for mood-appropriate songs
4. Lyrics Analysis: Fallback system analyzes song lyrics for emotional context
5. Audio Features: Librosa extracts tempo, key, and other musical characteristics
6. Recommendation: Personalized playlist generated based on detected mood

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🔧 API Requirements

To run this project, you'll need API keys from:

• Spotify for Developers - Music streaming and metadata
• YouTube Data API - Video content and metadata
• Google Gemini API - AI-powered emotion detection
• Genius API - Lyrics fetching and analysis

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📚 Acknowledgements

• Google Gemini API
• Spotify for Developers
• YouTube Data API
• Librosa
• Genius API
• Flask Framework

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👨‍💻 Developed By

Suman Naidu R, Yashaswini N P, Divya L

B.E. (Information Science), APS College of Engineering[2021-2025]

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🙋‍♂️ Contributing

Contributions are welcome! For major changes, please open an issue first to discuss what you'd like to change.

1. Fork the Project
2. Create your Feature Branch
3. Commit your Changes
4. Push to the Branch
5. Open a Pull Request

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