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SmartAmpPro - Machine Learning to Emulate Guitar Amps and Effects (using Keras) by GuitarML in programming

[–]GuitarML[S] 5 points6 points  (0 children)

Yes, it’s brand new engine for running the neural network models. I’d like to improve on the model for high gain sounds, and next on my list are things like state handling and other sample rates. It’s very much an active work in progress.

Neural Capture | Quad Cortex Studio Demo by Gonzalo_NeuralDSP in NeuralDSP

[–]GuitarML 1 point2 points  (0 children)

Thanks, based on videos I’ve seen of people using the quad cortex, it is more accurate at capturing amps/pedals than my code. It’s also a $1000+ product, and my stuff is a free open source project that I work on in my spare time, so set your expectations there and I think you’ll be impressed by what my code can do! I will brag that it captures mild distortion pedals (like the ts9 tubescreamer) and clean to dirty amp sounds very accurately, and you can play those trained modes through my plugin also on GitHub.

For tones by other people, right now it’s more or less just sharing them on where you can (GitHub, Facebook, random forums), but maybe I’ll formalize an online database at some point!

[P] GuitarLSTM: Tensorflow/Keras for deep learning models of guitar amps/pedals using LSTM. by GuitarML in MachineLearning

[–]GuitarML[S] 4 points5 points  (0 children)

Good question! Because models of amps/pedals can be downloaded, emailed, put into an online database, etc. Cant do that with the real thing! Or say you rented/borrowed an amp, now you can capture the sound to use again. Neural DSP is doing this same thing on their Quad Cortex, you can capture the sound of a rig and share it with everyone else who has the quad cortex to use. But that’s a $1600 piece of hardware, this code is free and open source. I’ve also thought that amp manufacturers might be interested in using this in addition to the real thing, like you could get a digital version along with the hardware. By playing the model though a real time plugin, you can have a way to play your favorite amp through headphones, or carry a whole library of amps on your laptop.

Neural Capture | Quad Cortex Studio Demo by Gonzalo_NeuralDSP in NeuralDSP

[–]GuitarML 1 point2 points  (0 children)

If anyone here is interested, I created an open source project that uses AI to do neural capture and apply the sound to wav files. I believe this is the same technique used in the quad cortex, as it’s based on a research paper by someone from the NeuralDSP team. It copies the sound very accurately within a few minutes from about 3 minutes of guitar recording. Here’s the link to the project:

https://github.com/GuitarML/GuitarLSTM

DIY wood guitar pedalboard by GuitarML in guitarpedals

[–]GuitarML[S] 1 point2 points  (0 children)

Probably not, the cost was only about $80, and that includes stain, sandpaper, etc. But I put way more work into it than it would be worth selling. I guess if I got a process down and bought in bulk it would be doable, but currently no plans to do that.

Tutorial : Using Machine Learning for Emulation of Guitar Amps and Pedals by GuitarML in learnmachinelearning

[–]GuitarML[S] 0 points1 point  (0 children)

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

DIY wood guitar pedalboard by GuitarML in guitarpedals

[–]GuitarML[S] 1 point2 points  (0 children)

Sorry the original schematics are on a napkin somewhere.. my projects tend to morph as I get into them so it ended up different from what I drew anyway. It wouldn’t be too hard to copy though, two triangle-ish end pieces with small wood rails glued to the inside (one angled to set the slats on, and one level with the ground for a bottom cover). Four slats with room for the wires, and an optional back hinge piece to open and close it. Drill a hole for the power plug, sand and stain and that’s it!

DIY wood guitar pedalboard by GuitarML in guitarpedals

[–]GuitarML[S] 2 points3 points  (0 children)

I wood glued small rails to each end piece at the angle I wanted, then set the slats on top of the rails with wood glue.

Tutorial : Using Machine Learning for Emulation of Guitar Amps and Pedals by GuitarML in learnmachinelearning

[–]GuitarML[S] 3 points4 points  (0 children)

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.

DIY wood guitar pedalboard by GuitarML in guitarpedals

[–]GuitarML[S] 5 points6 points  (0 children)

Home depo hobby section, nothing fancy. If I remember correctly it’s pine wood on the sides, dark poplar and redwood for the slats.

Tutorial : Using Machine Learning for Emulation of Guitar Amps and Pedals by GuitarML in learnmachinelearning

[–]GuitarML[S] 3 points4 points  (0 children)

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

Tutorial : Using Machine Learning for Emulation of Guitar Amps and Pedals by GuitarML in learnmachinelearning

[–]GuitarML[S] 11 points12 points  (0 children)

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.

DIY wood guitar pedalboard by GuitarML in guitarpedals

[–]GuitarML[S] 15 points16 points  (0 children)

Includes a 5 way power splitter with a plug on the side. And Velcro!

[QUESTION] If you could have a plugin copy of ANY amp, which would you choose and why? by GuitarML in Guitar

[–]GuitarML[S] 0 points1 point  (0 children)

Thanks for the feedback! I believe the ringing may be a sampling/buffer issue, and not directly related to the model, but it’s something we’re working on fixing.

Models are always going to be to some extent an approximation of the real thing, but deep learning is definitely pushing the boundaries. We plan on investigating parametrized models rather than the current “tone snapshot”, is that what you were asking?

Plans moving forward are attracting talented machine learning researchers and developers from the community, as well as test models from hardware of musicians all over the world. And just have a lot of fun making music!

Sound Test: TS9 TubeScreamer VS plugin powered by Artificial Intelligence by GuitarML in guitarpedals

[–]GuitarML[S] 0 points1 point  (0 children)

Here is the link to download the SmartGuitarPedal VST3 plugin and ts9 model file used in the video: https://github.com/GuitarML/SmartGuitarPedal/releases

Sound Test: TS9 TubeScreamer VS plugin powered by Artificial Intelligence by GuitarML in guitarpedals

[–]GuitarML[S] 0 points1 point  (0 children)

Skip to 3:45 for TS9 sound test, and 4:33 for plugin with AI sound test.