Literature Review : Emotion-Based Music Recommendation System with Age Detection

This research introduces an innovative Emotion-Based Music Recommendation System coupled with Age Estimation. Leveraging computer vision techniques, specifically Convolutional Neural Networks (CNNs), the proposed system analyzes facial data, obtained either through a camera or OpenCV, to discern both the emotional state and age of an individual. The synergy of emotion and age information serves as the foundation for personalized music recommendations. To compose playlists and propose songs, a third-party API is used, personalizing the musical experience to the user’s emotional state and age group. This integration of facial analysis, deep learning, and music recommendation aims to enhance user engagement and satisfaction by providing a more contextually relevant and emotionally resonant music selection.