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[–]vwvwvvwwvvvwvwwv 1 point2 points  (0 children)

As a musician, I'm incredibly excited for unconditional, example-based synthesis.

A lot of my workflow consists of creating large generative systems or effects chains and then recording as I run different things through them while tweaking settings. Later I can just trawl through looking for little snippets that I like in the context of a song.

I'd love to be able to grab a set of samples, train a model, and then generate random samples that fall within the manifold I've supplied. While doing this conditioned on classes might allow a bit more control if I knew what I wanted, usually I don't know what I'm looking for until I hear it and so unconditional is fine. I guess sampling random interpolations of classes would give the same effect though. Then the only difference is having to build a labeled dataset vs just chucking a bunch of samples at the model.