3/28/2023 0 Comments Deezer spleeterSpleeter is built with Python and TensorFlow, a popular combination for AI research. This really demonstrations computation in a way that we would see in real products – and it’s fast enough to incorporate into your work without, like, cooking hot waffles and eggs on your computer. With GPU acceleration, like even on my humble Razer PC laptop, you get somewhere on the order of 100x real time processing. (I like free stuff, in that it also encourages me to f*** with stuff in a way that I might not with things I paid for – for whatever reason. You can mess around with this without paying a cent, and even incorporate it into your own work via a very permissive MIT license. (You’ll just need some basic command line and GitHub proficiency and the like.) Spleeter from music streaming service Deezer (remember them?) is a proof of concept – and one you can use right now, even if you’re not a coder. But “we can map out ways in which this is working well now and make concrete plans to improve it with reason to believe those expectations can pan out” – yeah, that I’ll sign up for!) Start with a stereo mix – break it up into component stems. (“It will just keep getting better” is a logical fallacy too stupid for me to argue with. And it works – not perfectly, but well enough to be legitimately promising. It’s boldly going where no DSP has gone before, that is. And that’s unfortunate not because the technology is good at those things, but precisely because so far it really isn’t – meaning people may decide the thing is overhyped and abandon it completely when it doesn’t live up to those expectations.īut when it comes to this particular technique, neural network machine learning is actually doing some stuff that other digital audio techniques haven’t. It’s unfortunate in a way that people imagine that machine learning’s main role should be getting rid of DJs, music selectors, and eventually composers. Here’s where so-called “AI” is legitimately exciting from a sound perspective. You can hear the difference between the bassline and the singer – so why can’t your computer process the sound the way you hear? Splitting stems out of a stereo audio feed also demonstrates that tools like EQ, filters, and multiband compressors are woefully inadequate to the task. Wait a second – sure, you may not call it “source separation,” but anyone who has tried to make remixes, or adapt a song for karaoke sing-alongs, or even just lost the separate tracks to a project has encountered and thought about this problem. While not a broadly known topic, the problem of source separation has interested a large community of music signal researchers for a couple of decades now. There’s a funny opening to the release for Deezer’s open source Spleeter tool: The real power of machine learning may have nothing to with automating music making, and everything to do with making sound tools hear the way you do.
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