PERSONALIZED MUSIC RECOMENDATION BASED ON EMOTIONAL STATES USING YOUTUBE - M.SAI ADITYA,; P. VENKATESWARA RAO, (Utilitas Mathematica, 2025)
Music is a very influential medium that impacts human emotion in profound ways. The traditional music players need users to manually select songs while they lack the capability to detect emotional states automatically. This paper presents an AI, multimodal emotion-based music recommendation program which uses facial expression analysis to recommend music through a chat-bot from YouTube in real-time. This approach uses a combination of an image- based Haar cascade classifier for emotion recognition and a fine-tuned Hugging Face model to improve accuracy in predictions. The chat-bot will use keyword-based Natural Language Processing to simulate a conversation with the user to improve emotion detection by analysing text.