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What is Emotion-Based Music Recommendation System Integrat about?

This article presents an emotion-based music recommendation system that integrates facial expression recognition (FER) and lyrics sentiment analysis using a Convolutional Neural Network (CNN). The system achieves a FER accuracy of 91.78% and utilizes a curated music dataset to classify songs into seven emotional categories, enhancing personalized music experiences. The study aims to address the limitations of existing music recommendation systems by providing tailored playlists that align with users

Author

thememeboaster

Language

EN