Enhanced Facial Emotion Recognition Based Music Selection Using Deep Learning

Music has a powerful influence on emotions, shaping moods and enhancing overall well-being. This paper introduces the idea of an emotion-aware music recommendation system that uses facial emotion recognition (FER) to suggest music based on a user’s real-time emotional state. Unlike traditional systems that rely on past preferences, this approach dynamically adjusts music choices to reflect how the user is feeling in the moment, creating a more personalized and immersive experience. With potential applications in mental health support, interactive AI systems, and entertainment, this technology could help reduce stress, boost mood, and enhance engagement. However, challenges such as ensuring real-time accuracy, diversifying datasets, and addressing privacy concerns need to be considered for broader adoption. By combining emotion recognition with music selection, this system aims to revolutionize digital interactions, making them more intuitive, emotionally responsive, and user-friendly.