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With all the buzz over machine learning and 'the classification problem' it might be interesting to run something like a waveform classifier trained on large mu
by photochemsyn 4y ago
With all the buzz over machine learning and 'the classification problem' it might be interesting to run something like a waveform classifier trained on large music collections, i.e. on the binary files themselves, - at least as a means of discovering new music one likes (probably wouldn't solve the metadata problem as described in the article however, that's more of an archival issue it seems).
- Spivak 4y agoI think you’re describing https://maroofy.com/ https://maroofy.com/ But the bigger issue is that while it’s pretty good at finding songs that sound similar it’s not great at finding songs that are musically similar. But nonetheless I really appreciate a novel recommendation algorithm that’s not based on popularity. I’ve gotten good recs from this site with with less than 10 monthly listeners which is super cool — I’ve never been so underground.
- JohnFen 4y agoA couple of decades ago, I ran a crawler that would go out and find music I like for me. It used pretty simple heuristics to identify what "I like". It was actually really great, and I found a lot of fantastic music from really obscure musicians that there was zero chance I would have ever stumbled across otherwise. Then it was improved to make the matching even more accurate, and it was -- but that made it less useful to me. It turned out that the inaccuracy was a feature, not a bug. When the matching got too good, I started getting music that was too much like the stuff I told it I liked, and I stopped finding so much great stuff that would have escaped me before.