Today let’s talk about the largest on-demand music service application today i.e. Spotify and how it uses the concept of Artificial Intelligence and Machine Learning to enhance the user experience.
If you’re frequent users of Spotify, you might have noticed “Discover Weekly” playlist which is updated weekly with new recommended songs , this personalized feature is due to usage of three models which are as follows:
- Collaborative Filtering
- Natural Language Processing
- Audio Models
Let’s understand the use of each model and how it contributes toward personalized experience
Let’s first understand what Collaborative Filtering is :
It is a method of making automatic predictions(filtering) about a particular user ‘s interest by using the preference or taste information from multiple users.
In case of Spotify, this method powers their recommendation models , it uses implicit feedback like
- the number of times a song is played by a particular user
- the songs saved to the list by the user
- artist’s page when their song has been listened
It helps Spotify to provide relevant recommendations to the similar users
Natural Language Processing
Natural Language Processing is the ability of a computer program to understand human language as it is spoken.
In case of Spotify, analysis of human speech is done via text . It scans a track’s metadata that includes the following
- Blog posts and discussions about a specific musicians
- News articles and people’s review about certain artists or song and the language being used
Using the above metadata, it identifies descriptive terms like noun, phrases and other texts associated with those songs or artist
Then , these keywords are categorized into “cultural vectors” and “top terms”. Each artist and song is associated with thousands of top terms and they are subject to change on a daily basis. Also each terms is assigned a weight, reflecting its relative importance in terms of how many times an individual would attribute that term to a song or musician they like.
In Spotify, audio models are used to analyze data from raw audio tracks and categorizes songs accordingly. Also they help the platform to evaluate all songs and create recommendations accordingly.
These are the ways in which Spotify leverages the power of AI to make a powerful recommendation system to enhance user experience.
Thank You !!!
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