How Spotify’s Algorithm Knows Exactly What You Want to Listen To

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        How Spotify’s Algorithm Knows Exactly What You Want to Listen To
        A set of powerful algorithms use your music and your personal details to sh

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        Spotify is doing everything it can to get you to listen to more music.
        The company has created algorithms to govern everything from your personal best home screen to curated playlists like Discover Weekly, and continues to experiment with new ways to understand music, and why people listen to one song or genre over another.
        Spotify needs to continue building out these algorithms because it’s the only way to create custom listening experiences for each of its over 200 million users.
        Its whole purpose is to give you music that Spotify is confident you’ll like, based on your previous listening activity.
        But Spotify also has to drop in new, fresh music so you don’t get stuck in a loop of listening to the same thing all the time.
        But when Spotify explores, it uses the information about the rest of the world, like playlists and artists similar to your taste in music but you haven’t heard yet, the popularity of other artists, and more.
        Spotify intern Sander Dieleman, who worked at the company in 2014 and did some foundational work analyzing the auditory similarity of music, also explained the audio analysis algorithm in a personal blog post.
        The original problem was that new music was uploaded to Spotify every day, but there was no system to recommend music if it wasn’t by a previously popular artist.
        The team has also worked on aligning written lyrics to the moment in a song where the lyric is sung, which could not only help with the company’s Behind the Music feature that shows lyrics alongside popular songs, but also open up new opportunities for Spotify.
        “Time-aligned lyrics can enrich the music listening experience by enabling karaoke, text-based song retrieval and intra-song navigation, and other applications,” Spotify computer scientists wrote earlier this year


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