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Deep Learning for Guitar Effect Emulation

teddykoker.com

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Re: Deep Learning for Guitar Effect Emulation

#71
I play guitar and own a tube amp & a tube screamer.

All of this sounds horrible.. it doesn't even sound like his input is an actual guitar, it sounds like he's using a synth guitar sound or something. There's no dynamics, almost no sustain, no articulations. The outputs barely even sound distinguishable as a guitar through a tube screamer, even his actual tube screamer samples. (Possibly cause his interface is terrible?)

The conclusion is ridiculous given how simplistic everything is.

You can't use two tiny little clips to justify your model being high quality.

The true test has to even allow a bunch of guitarists to move all the knobs, plug the model into different amp & guitar combinations, put other effects in front of and behind it, etc..

The Tube screamer is called a Tube screamer because it's intended use case is to make the tubes in a tube amp "scream". Using it with all the knobs at noon is not consistent with this, it usually gets used with a tube amp that is already on the verge of distortion, and then you use the TS with the volume turned up a lot (3/4-max) and the gain quite low, this might be part of why this sounds so bad to me.

There are actually two different trains of thought on guitar effect modeling:

- Model it based on input & output waveforms like he's doing

- Actually model the circuit as an electrical simulation and then pass the signal through that.

I have personally found the second approach to be way more realistic and satisfying. The Yamaha THR amps work this way and they're really amazing.

One of the tricks here is a listener might not be able to tell a difference, but the guitar player picks up on a perceived change in how the guitar feels with these effects. A tube screamer has a lot of compression built into it for example. It causes everything to play to sound a little dirtier for the same amount of picking energy you put into the guitar. It will cause the player to play a little more lightly than they would without the effect. This is the kind of thing that makes a player reject the model and want to stick with the real thing, whereas the guy in the naive lab building the model thinks it's great cause they're not even playing an actual guitar through it. Once a skilled player tries it the "feel" is a dead giveaway which is which.

It's easy for some of this stuff to get lost on the electronics crowd if the background is electronic music. An actual acoustic piano is the only keyboard based instrument that has anywhere near the nuance that a guitar has, and a guitar still has way more weird stuff going on with dynamics and articulation. The range of inputs you have to feed into any kind of computer model to simulate guitar well is huge.

Re: Deep Learning for Guitar Effect Emulation

#72
post #67
post #8

> We find that the model is able to reproduce a sound nearly indistinguishable from the real analog pedal. Maybe for the average person or buried in the mix, but the audio samples were easy to distinguish for me as a guitarist. The NN samples unnatural decay were a dead give away.

Not really a guitarist, but listening to them I couldn't hear a specific difference. Yet I still liked one of them more. And when I clicked "reveal" that one was the real one, turns out.

the real one has longer fading tones, the one generated by machine learning cuts the sound abruptly.

it seems easy for me to differentiate them and I’m a beginner with guitars (~1 month, so I’m your average Joe). it’s pretty good though, I’m sure it can be improved greatly.

Re: Deep Learning for Guitar Effect Emulation

#73
post #3

Pretty cool, though I wonder what the latency of this would be if used as a plugin? The author says it works in real-time, but to non music/audio folks this could mean '100 ms latency is real-time enough, right?' Generally, I think the audio VST business is a really fun space to be in for a lifestyle business, as it is way too small to be attractive for VCs. It seems like a space that provides many niches for lots of…

while training? terrible. As finalised model running in an AU/VST3 wrapper? probably extremely low.

Re: Deep Learning for Guitar Effect Emulation

#74
post #3

Pretty cool, though I wonder what the latency of this would be if used as a plugin? The author says it works in real-time, but to non music/audio folks this could mean '100 ms latency is real-time enough, right?' Generally, I think the audio VST business is a really fun space to be in for a lifestyle business, as it is way too small to be attractive for VCs. It seems like a space that provides many niches for lots of…

Do solo or small shop vst plugin developers make any money? I’m curious if anyone has any direct knowledge about that. There are so many professional activities similar to that where no one makes any money and people really just do it for the love, and then there are seemingly similar things like that where people make surprisingly large amounts of money.

They do. Strezov sampling is one guy. Serum is one guy. Chris Heinz is one guy, etc. etc.

But you have to be willing to put in the time and make phenomenal products, because no one wants average instruments and effects, we can get those for free.

Re: Deep Learning for Guitar Effect Emulation

#76

"many purists argue that the sound of analog pedals can not be replaced by their digital counterparts." Truly effective modelling of analog pedals, tube amps and guitar cabs has been around for years and is way more cost effective from the bedroom to touring bands. The "purists" are hipsters who value the rarity of some pedals, massive pedalboards and their tube amps. I'm not knocking them - I understand why there is…

I am by no means a musician or an experienced one at that. I tinker and enjoy playing and learning. But I have limited experience overall.

My personal experience with electronic tools is the lack of feel. Can I make music with digital tools like AxeFX and similar? Absofreakinglutely. No doubt about it.

But those digital tools feel VERY different to me than the real thing. I'm not just talking about a speaker moving air, though that's certainly part of it. My tube amp simply responds differently than any digital model of a similar amp.

I find tools like the Kemper to be amazing, but they're just a snapshot of an amp in a particular configuration in a particular room.

From a technical standpoint, all this modeling stuff is super cool. But it doesn't feel the same at the end of the day and this is a personal opinion and preference on my part.

I look forward to the day that I can get an amp in a pedal (like the Strymon Iridium) and it behaves the same as the real amp. I think Fender's Deluxe Reverb (Tonemaster model) is as close as it has ever gotten, but it very specifically emulates a single amp and does so within a real amp cabinet rather than pushing it out to an audio interface.

Anyway, anything that gets people playing guitar is, in my opinion, a great thing. We live in a golden age of guitar equipment. I don't think it can honestly get much better than it is right now. It's an amazing time to be a guitar player and incredible options are available at amazing prices.

Re: Deep Learning for Guitar Effect Emulation

#77

"many purists argue that the sound of analog pedals can not be replaced by their digital counterparts." Truly effective modelling of analog pedals, tube amps and guitar cabs has been around for years and is way more cost effective from the bedroom to touring bands. The "purists" are hipsters who value the rarity of some pedals, massive pedalboards and their tube amps. I'm not knocking them - I understand why there is…

I'm a guitar noob, but have been wanting to pick up an electric for ages :).

Quick question - how does that Axe-FX compare to various Amp emulators such as AmpliTube, Line 6 Helix Native, Guitar Rig, Positive Grid BIAS Amp, S-Gear, etc... ?

Re: Deep Learning for Guitar Effect Emulation

#78
post #3

Pretty cool, though I wonder what the latency of this would be if used as a plugin? The author says it works in real-time, but to non music/audio folks this could mean '100 ms latency is real-time enough, right?' Generally, I think the audio VST business is a really fun space to be in for a lifestyle business, as it is way too small to be attractive for VCs. It seems like a space that provides many niches for lots of…

I assume by real-time he meant "able to produce samples at a rate equal to or higher than the audio output sample rate".

That's not what real time, means though. Real time processing means taking signals as they come in, and outputting the transformed result such that there is as close to no signal lag as possible. The output can in fact be wildly lower or higher resolution, real-time does not particularly say anything about that. It's all about whether the output plays (for practical purposes) at the perceived "same time" as the input signal. There will always be some delay, but that delay can't get perceivable, and for obvious reasons there can't be any (significant) buffering.

Re: Deep Learning for Guitar Effect Emulation

#80

"many purists argue that the sound of analog pedals can not be replaced by their digital counterparts." Truly effective modelling of analog pedals, tube amps and guitar cabs has been around for years and is way more cost effective from the bedroom to touring bands. The "purists" are hipsters who value the rarity of some pedals, massive pedalboards and their tube amps. I'm not knocking them - I understand why there is…

I think what you mean by 'hipsters' is 'professionals'. As someone who's made several records and been in many recording studios, I would challenge you to name a single record that does not utilize an analog signal chain, for mastering at the very least. VST modeling is great when you want a super clear tone and is very popular in certain genres. But definitely not ubiquitous and certainly not superior tech. Digital just don't SLAP like analog.
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