Using LiveSPICE to train ML models #171
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I think that we can utilize the
That's what we have already 😁 I'm actually trying to do the opposite. I've currently loosen the Newton iteration relative delta condition from 1e-4 to 1e-3 without any noticeable negative impact on stability, but in your case you might want to try the opposite. We should probably make it a settable parameter. |
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Very cool idea and work! Agreed that some kind of command line interface is probably the most useful tool here for batch processing lots of data. We can either add audio file IO support to our own command line tool, or perhaps the more expedient approach is to leverage your VST work and use existing software/workflows to generate lots of files. The first option is really easy to get something quickly working. .wav files are trivial to read/write, and libraries for other formats are probably readily available. The tests already run circuits on buffers of data, it doesn't take much code, and adding a way to set circuit parameters via command line arguments doesn't seem hard either. The VST approach would probably offer a lot more features and tools, but I don't know if we actually need them for this... |
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Lately I've been using (and assisting with the development of) Neural Amp Modeler - a framework for training and real-time playback of NN-based models of amplification equipment. It works really well.
A while back it occurred to me that LiveSPICE could be used to generate training data, and I finally got around to doing it:
https://blog.nostatic.org/2023/04/this-boss-sd-1-pedal-does-not-exist.html
Any thoughts on improvements to LiveSPICE to facilitate this use case?
A few thoughts I had:
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