Hey, Chris here, I run Musosoup. Quick question for anyone working with ML and audio. At the moment we’re tagging genres manually when tracks come into the platform, and artists add their own too. It ends up being pretty inconsistent and obviously doesn’t scale. I’ve been looking into whether this can be automated. I haven’t gone deep on it, just watched a few things and read around a bit, but what I saw didn’t seem that accurate. That said, I might be way off or looking in the wrong places. Just wondering if anyone here has actually built something like this, or knows of anything decent that can take a track and assign genre(s) in a reasonably reliable way, especially with crossover or niche stuff. Also curious whether people are training on labelled datasets like Discogs, or going more down the similarity / embeddings route. Would appreciate any pointers, or even just a reality check on whether this is actually workable right now. Cheers submitted by /u/chrismusosoup
Originally posted by u/chrismusosoup on r/ArtificialInteligence
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