Live data from Hacker News

Spleeter: Extract voice, piano, drums, etc. from any music track

github.com

21–30 of 182 posts

Re: Spleeter: Extract voice, piano, drums, etc. from any music track

#23
post #11

Is there anything like this for images? Meaning essentially trying to decompose back into photoshop layers. Wouldn't be feasible for lots of stuff that is completely opaquely covering something, but I'm thinking for things like recoloring a screen print, etc.

I have no idea how I managed to re-find these, but I did. Two recent moderately-related/relevant posts:

https://news.ycombinator.com/item?id=20978055

https://news.ycombinator.com/item?id=21220458

Re: Spleeter: Extract voice, piano, drums, etc. from any music track

#25

I gave a talk at pycon this year about dsp [1], specifically some of the complexities surrounding this. I came across a few other ml projects that claimed to do this as well, and the biggest hold up is getting enough properly trained data, tagged appropriately, in order to let the models train correctly. in the git repo of this project they also explicitly state you need to train on your own data set, though you can…

I'm sure you've thought of this, but could/have the tracks from the Rock Band games be used for training?

There are thousands of them and they're separated into different instrument tracks. They even had bands re-record songs sometimes where seperate masters couldn't be found. If I recall correctly, Third Eye Blind did this for Semi-Charmed Life.

Re: Spleeter: Extract voice, piano, drums, etc. from any music track

#26
post #24
post #22

Wait the implications of this are huge for electronic music DJs

The audio (^F soundcloud) sounds a little warbly... if that can be largely mitigated, then yes, remixes will never be the same

While not great, the phase smearing is orders of magnitude better than most vocal isolation plugins I've used. I only expect it to get better. Very cool!

Re: Spleeter: Extract voice, piano, drums, etc. from any music track

#28
Not only are the results good, but the music is generated decently rapidly. The implications are clear: whoever wants to make a quick fortune on YouTube should start converting and uploading truckloads of songs as fast as possible. The demand is there. I could easily see that bringing in millions of views.
Post reply on HN