Emotion-Based Music Recommendation System
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Description:
An emotion-based music recommendation system suggests songs based on the user's emotional state, which can be detected through facial expressions or input preferences. Machine learning can be used to classify emotions and recommend music accordingly.
Features:
- Detect user emotion through facial expressions or text input (using emotion detection models).
- Recommend music based on the detected emotion.
- Integrate with streaming platforms like Spotify or YouTube for music recommendations.
- Customize music playlists based on user preferences and historical data.
Requirements:
- Programming Language: Python
- Libraries/Tools:
- OpenCV and deep learning models for emotion detection.
- Scikit-learn or TensorFlow for emotion classification.
- Spotify API for fetching music recommendations.
Instructions:
- Train or use a pre-trained emotion recognition model (e.g., from facial expressions or text).
- Integrate the emotion classifier with a recommendation engine (e.g., Spotify API).
- Display music recommendations based on the detected emotion.
License:
For personal and professional use. You cannot resell or redistribute these repositories in their original state.
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