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@article{169128,
        author = {Anuradha Gethe and Shravani Deshpande and Ankit Bhamare and Aditi Dhumal and Dr.P.D.Halle},
        title = {Playlist Generator using Facial Expression},
        journal = {International Journal of Innovative Research in Technology},
        year = {2024},
        volume = {11},
        number = {6},
        pages = {365-367},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=169128},
        abstract = {The playlist generator creates music playlists based on the user’s facial expression or mood to create music that matches their current mood. This study investigates a system that creates music playlists based on facial recognition. The system analyzes the user in real time and matches the user’s current mood with compatible songs from a selected library. The goal is to create personalized playlists that improve mood and enhance user experience. Research focuses on the accuracy of emotional intelligence, the impact of visual feedback, and user satisfaction. The electronic playlist using facial recognition is an innovation designed to enhance the user experience in music therapy by analyzing emotions using facial recognition technology. The system is designed to create personalized playlists that match the user’s current mood, as determined by instant facial analysis. The system is based on facial recognition, which can process and interpret multiple faces to show emotions such as happiness, sadness, anger, and grief. The mood data is then matched with a predefined library of music genres, tracks, and moods. The system dynamically creates playlists that correspond to the emotional state, offering the user music options that match their current emotions.},
        keywords = {Emotion Recognition, Playlist Generation, Personalized Music, Emotional Analysis, Machine Learning, Computer Vision, Mood-Based Music, Adaptive Algorithms, Real-Time Emotion Detection, User-Centric Music Recommendation.},
        month = {November},
        }