Emotion Based Music Player Using CNN

Abstract

Abstract: This work presents a music recommendation system that suggests songs based on the user's emotional state. The system uses computer vision techniques to detect the user's emotions through facial expressions, and a suitable song is recommended accordingly. The proposed system automates the traditional manual process of selecting music based on mood, reducing time and effort. The algorithm uses Haar Cascade and CNN algorithms to detect facial expressions and select an appropriate music track. The inbuilt camera reduces system design costs. The system is based on recommender systems, convolutional neural networks, deep learning, image processing, artificial intelligence, and classification.