ddsp VS awesome-python-scientific-audio

You can actually use thousands of oscillators, which is what Magenta did with their differentiable DSP (DDSP) approach to modeling acoustic instruments including singing:

https://magenta.tensorflow.org/ddsp-vst

https://magenta.tensorflow.org/ddsp

I doesn't sound realistic but it is expressive in an unusual way.

Have you checked out DDSP from magenta? I’m not sure what kind of learning you are trying to implement but they provide a lot of standard signal processing components that are differentiable so you can use them as part of a neural net. There are a handful of collabs that serve as interactive tutorials and the documentation is not bad, I did my bachelors thesis on the topic so I got quite stuck into this for a while

In case you're asking about the parent comment (s/Differential/Differentiable), it means the title should be "differentiable CV" (instead of "differential CV").

"Differentiable" describes some computation for which derivatives can be computed. "Differential" is a more general term which means that something has to do with differences, e.g. differential equations deal with equations that specify how things change together.

With the recent surge in deep learning came significant improvements in optimization techniques and hardware, making it feasible to formulate some computations in a differentiable manner. Doing that allows one to optimize the computation process relatively efficiently, at least in theory. Some other examples: differentiable programming[0] (other differentiable techniques are a subset of this), differentiable rendering[1], differentiable signal processing[2].

[0] https://en.wikipedia.org/wiki/Differentiable_programming

[1] https://arxiv.org/abs/2006.12057

[2] https://github.com/magenta/ddsp

Here is a great list awesome-python-scientific-audio. Many people dive into deep learning, while a lot of projects can be done with signal processing. I have used PyDub, Librosa, and PYO on a few non-deep learning projects, which are quite fun. Also, once you get your audio into python, play around with NumPy and create some of your own processes.

https://github.com/faroit/awesome-python-scientific-audio#readme