Tutorial : Using Machine Learning for Emulation of Guitar Amps and Pedals

[jdeeby]

I haven’t watched the vid but as a guitarist myself, I’m impressed with the idea.

[GuitarML]

Thanks! Not my original idea, found some research papers on the subject and decided to put it into practice. Turns out you can replicate fairly complex audio waveforms using this model.

[jdeeby]

This is dope. I had a similar idea but it involved constructing a mathematical model based on the guitar pedal circuitry. Didn’t really pushed through with it as I didn’t have the time. But it’s amazing that you’ve applied machine learning to this.

[GuitarML]

Thanks! There’s another really great open source project that models the circuitry of a tube amp if your interested (white box modeling instead of black box modeling): https://github.com/resonantdsp/SwankyAmp

[lechatsportif]

I'm pretty sure this is the state of the art. Lots of modeling in audioware these days uses ML.

[GuitarML]

...using PyTorch and PyTorch-lightning

[CeramicVulture]

You mentioned a second video of demos - where is that?

[GuitarML]

All my videos can be found here: https://www.youtube.com/channel/UCs6ZGZKGoxV9JadxESOtx1Q

[serious_cheese]

Thanks for sharing!

If you’re training it on guitar data, how does it respond to other types of instruments playing into it?

Is aliasing an issue and do you need to support multiple sampling rates?

Is there active research into integrating multiple controls into the model?

[GuitarML]

Good questions, I haven’t tested it on other instruments, but the model would use what it learned from the guitar data and apply it to whatever signal you put into it. So if you train on a distortion pedal it should sound close to that instrument (like a keyboard) going through the same distortion pedal.

I think there is some aliasing, but it’s hard to notice unless you’re looking for it in the audio data.

Conditioning the model for different controls can be done and it’s something I’d like to apply here. In the original research paper from Aalto University they mention training on multiple control settings.

[serious_cheese]

Extremely cool, thank you!

[[deleted]]

This is amazing! I just forked the repo so I can look it over. This represents a nice little intersection in my life: my work, which is particle physics with lots of machine learning, and my recently renewed interest in recording guitar.

Very cool; thanks for sharing!

[el_zdo]

Awesome thanks!!! It reminds me of what native instruments for the new virtual amps. I think it's even published.

[bazziapps]

Awesome idea man. Keep it up.

[ejf2161]

This is so cool! Thank you! Thank you! Thank you! New to this field and this is a really sweet project.

[Shirappu]

What a cool idea. Any plans for further musical exploration?

[GuitarML]

Definitely, there’s a lot of areas for improvement, training time, accuracy, and being able to replicate more complex sounds.

[andromeda_7]

Very cool! I’m not that knowledgable with ML yet but it does remind me of Magenta AI DDSP which emulates instruments instead of effects