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Show HN: I trained an AI model on 120M+ songs from iTunes

maroofy.com

21–30 of 444 posts

Re: Show HN: I trained an AI model on 120M+ songs from iTunes

#21
That is a great idea! Measuring distance between embeddings has always been a cool concept (ex. If I have a vector that represents the word "king" and from it subtract the vector that represents "man" then add the vector that represents "woman" it will approximately equal the vector for "queen") and it's awesome to see the same concept applied to music.

Most other services try to find matches by seeing what other songs the people who like the searched song like, and finding trends amongst those. This site finds songs with similar sounds and rhythms by looking in the vector space. Awesome! Congrats on the finished site!

Re: Show HN: I trained an AI model on 120M+ songs from iTunes

#24
This is very interesting, but unfortunately I haven't had the greatest luck in finding new songs I would enjoy listening to. It absolutely finds similar sounding tracks, but it doesn't distinguish which part of the song made it enjoyable. There's no tempo consistency or genre consistency or even main instrument/vocal timbre consistency between recommendations. I think locking one or more of those dimensions would allow for much better recommendations. I'm not sure what aspect you're using to order the results, but having extra metadata to filter or group the results in some way would help a lot.

Take Raga's Dance by Vanessa-Mae, A R Rahman, ... Royal Philharmonic https://maroofy.com/songs/476841571 . I put in this track expecting other fusion songs to pop up, and arguably some do, but much more often it feels like a 20 second section was used to define the original song and it misses the underlying concept. Like it got, in my subjective description, the epic violin in orchestral music, but it completely ignores the fusion between the distict styles of traditional indian singing/instrumentals and western ochestral and also ignores the call response structure between the violin and carnatic players, which is the what I actually care about. Other songs have the vocals but no epic backing. It feels like it's matching multiple samples from the song instead of the whole song.

This feels very promising since it clearly is picking up the styling of the specific songs across different genres and languages. I look forward to seeing where this goes.

I also think it would be interesting if there was a way to specify two different songs to find either only the common things and/or to find what the fusion of those two tracks produces.

Re: Show HN: I trained an AI model on 120M+ songs from iTunes

#26
post #15

How did you download that many songs? Wouldn't that be something on the order of 360 terabytes?

I guess he is working with the 30s low rez previews, I know you can download them with the Spotify API. Apple Music should be similar.

Wouldn't this still be about 36 terabytes of data?

Re: Show HN: I trained an AI model on 120M+ songs from iTunes

#28
Tried with a song I knew well- Everything In Its Right Place.

Feels a little bit like fortune telling, I guess it is, in the sense that I am listening closely to what makes the songs similar, not just listening, but actively trying to find the similarities, so even a couple notes in progression, or drum-beats and I'll say oh, yes, that matches.

Finds very different music, not necessarily what I'd listen to in many cases, but kudos for getting me clicking through a decent pile before going wait, that's a nope, you're grasping AI-type-being.

Re: Show HN: I trained an AI model on 120M+ songs from iTunes

#30
Interesting idea, I get pretty average recommendations though.

The first track I searched for was "Hazmat Modine - Bahamut" (https://maroofy.com/songs/253108933), it seems to recommend things with some similar instruments (e.g. brass and sax) but not really similar taste or style.

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