That raises an interesting difference between cleaning AI-generated sound and cleaning ordinary recordings. In an ordinary recording, there is an objective reality to discover -- a certain collection of voices was summed to create a signal. With (most? the best?) existing AI audio generation, the waveform is created from whole cloth, and extracting voices from it is an act of creation, not just discovery.

I've come across AI-generated music that outputs something like MIDI and controls synthesizers. Its audio quality was crystal-clear, but the music was boring. That's not to say the approach is a dead-end, of course -- and indeed, as a musician, the idea of that kind of output is exciting. But getting good data to train something that outputs separate MIDI-ish voices seems much harder than getting raw audio signals.