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Code for the paper Hybrid Spectrogram and Waveform Source Separation, but the goddamm motherfucker doesn't work.
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Some of you have probably heard of spleeter, a machine learning program developed by Deezer that isolates instruments. It was pretty good, but it had some obvious weaknesses. But what if I told you that there's something even better? Ultimate Vocal Remover is so good I audibly said "holy sh*t" when I listened to what it produced. It recently released a full-band model (UVR-MDX-NET Inst HQ 1), unlike spleeter which has an 11kHz cutoff.
Some of you have probably heard of spleeter, a machine learning program developed by Deezer that isolates instruments. It was pretty good, but it had some obvious weaknesses. But what if I told you that there's something even better? Ultimate Vocal Remover is so good I audibly said "holy sh*t" when I listened to what it produced. It recently released a full-band model (UVR-MDX-NET Inst HQ 1), unlike spleeter which has an 11kHz cutoff.
This is based off of https://github.com/facebookresearch/demucs which does sound better than Spleeter, but largely just because it's latest generation is newer. The next big update to Spleeter will probably be better than this and then the next update to this will be better than that, etc.
UVR does include support for demucs (including the latest version, v4); however, the model that OP is recommending is mdx-net, which is a completely different AI model. mdx-net can produce superior vocal stems, but it can separate into only two stems (vocals, other).
There are other GUIs for demucs, such as StemRoller, but UVR is by far the most versatile one. One great feature of UVR is the ability to use set up “ensembles” that use a different AI model for each individual stem.