Music Recommendation System Based on User’s Facial Emotion

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Nevon Driver Drowsiness Detection System Using Python
nevon software

Music has always been known to change people’s moods. Capturing and recognizing a person’s emotion and displaying appropriate songs matching the person’s mood can gradually calm their mind and end up giving a pleasing effect.

People express their emotions primarily through their facial expressions. Our system aims to capture a person’s emotion through facial expressions. The user’s current emotion is used to generate an automatic music playlist. When compared to the algorithm in the existing literature, it performs better in terms of computational time.

In this system, the user can chat with the chatbot. The emotion will be detected and the music player will start playing particular music. The person should be in the area containing light so that the detection is clear. The main objective of our music recommendation system based on users’ facial emotions is to provide users with suggestions that match their preferences.

The front-end involves Html, CSS, and JavaScript and the back-end involves Python. The framework used is Django and the database is MySQL. The libraries are OpenCV, Dlib, and TensorFlow. The algorithm implemented is CNN.


  • It’s easy to maintain.
  • It’s user-friendly.
  • Emotions are detected using the facial expression of users.
  • Instant music recommendation.