Feature Selection based Music Selection using Artificial Intelligence

Abstract

Music recommendation systems have become increasingly popular in recent years thanks to artificial intelligence (AI). Streaming services have become increasingly popular in recent years thanks to affordable internet and media streaming services. Because the user base of music streaming services is ever-growing and the market in streaming services is also competitive, it is critical to provide listeners with recommendations to increase user base retention. Music recommendation systems have come a long way in the last decade, but there are still several issues to be addressed. Pure sound-based recommendations may have been a good option to examine. It would have been advantageous to explore pure sound-based recommendations since they would have been more accurate. The current systems available to consumers also have significant advantages, such as collaborative filtering of listeners, based on location, artists' preferred genres, etc., and recommending songs based on the results. Collaborative filtering does produce great results. This sound-based approach might achieve greater results when combined with these current methods.