AI has Changed the Definition of Personalized Music Recommendations

Music streaming apps today use artificial intelligence in analyzing listening preferences of users, as a way to personalize a curated list of recommendations. Some AI’s can even detect a streaming app user’s current activity, or even the weather condition where a listener is currently located.

That is why music tech companies like QQ Music, Joox, KKBox and similar music technology providers are experiencing growth. The uptake of AI in music recommendation and streaming applications has changed the way personalized music is being delivered.

How Has AI Improved the Music Listening Experience of Music App Users

AI-based music recommendation engines are into analyzing the history of app users when recommending new songs.

A feedback mechanism can automatically indicate how a song or melody can affect a listener’s health vitals, as a way to improve the curated results that the recommendation engine will deliver. The purpose of which is to come up with different music genres, melody, harmony, tonal quality, and rhythm that complements the listener’s body vitals, supposedly to create a healing or uplifting effect.

Since every musician presents their personality through their music, the AI’s filtering mechanism does not limit personalized recommendation to a single genre. Personalization gets to have a whole new definition as the playlist generated will consist of unrelated songs deemed as “good music” by every individual.

Based on the personality feedback generated by the filtering engines, scans of thousands of newly uploaded will aim to develop a playlist to eliminate the need for streamed music listeners to browse through a multitude of choices when selecting their favorites.