Show HN: I trained an AI model on 120M+ songs from iTunes
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.<p>Take Raga's Dance by Vanessa-Mae, A R Rahman, ... Royal Philharmonic <a href="https://maroofy.com/songs/476841571" rel="nofollow">https://maroofy.com/songs/476841571</a> . 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.<p>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.<p>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.