Aaroha: A Music Recommendation System

Abstract

Abstract: The increasing availability of music streaming services has led to a vast collection of music. However, this abundance of music can make it difficult for users to find new songs and artists that match their tastes. Music recommendation applications provide a solution to this problem by using various algorithms and techniques to suggest music based on the user's listening habits and preferences. In this research paper, we review the popular music recommendation applications and the methods they use to recommend music. We also propose a new music recommendation system based on the user's emotional state and implement it using machine learning techniques. Our results show that our proposed system outperforms existing music recommendation systems and provides a more personalized recommendation.