jessejengel

10 ms·

1.
Turn Anything into a Musical Instrument(g.co)
10 points by jessejengel 6y ago|0 comments
2.
by jessejengel 7y ago
Coincidentally, that's how I came around to it, from a physics undergrad, to music software, to cs.
3.
by jessejengel 7y ago
Hi, yup that's true we keep the filter order fixed. For the experiments in the paper, the time-varying coefficients are generated by a neural network that is trained end-2-end to generate audio like the training set (conditioned on hig
4.
by jessejengel 7y ago
DDSP modules are helpful in situations where you want to impose some level of interpretability and modularity. Most also don't have parameters themselves, but must have them provided by another network or variable. So you could imagine
5.
by jessejengel 7y ago
Sorry about that :), definitely an interesting coincidence. Funny enough we actually were thinking of naming dDSP (as in derivative of DSP) but had already submitted the ICLR paper so just stuck with all caps (also because python is all low
6.
by jessejengel 7y ago
Hi I'm Jesse, one of the authors, thanks for the interesting questions! - In terms fo the FIRs, I think you can think of this as a form of more general/nonlinear filter modeling. The difference being I think that you can have a fi
7.
DDSP: Differentiable Digital Signal Processing(twitter.com)
14 points by jessejengel 7y ago|0 comments
8.
Making a Neural Synthesizer Instrument(magenta.tensorflow.org)
147 points by jessejengel 9y ago|44 comments
9.
Efficient Neural Networks Without the Math(svail.github.io)
4 points by jessejengel 10y ago|0 comments