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Nam: Neural network emulator for guitar amplifiers

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Re: Nam: Neural network emulator for guitar amplifiers

#11

Post by earthnail »

Bad_CRC wrote: post #10
TomWhitwell wrote: post #6

Earlier quoted context omitted.

Is it fair to say this clones a device with one specific set of knob positions? So if I want to clone a 5 knob fuzz pedal in every possible setting, that’s a lot of cloning to do? I may have misunderstood.

With the Kemper Amp (a profiling amp) it goes through a series of "noises" to get a profile: https://www.youtube.com/watch?v=iL7tWFhH8E8 But yes, you get the sound of a specific EQ settings.

The Kemper amp is mathematically super elegant. Two matrices A and B, and one nonlinearity in between. That’s it. All the noise profiling does is figure out A and B, which correspond to the impulse response before and after the distortion.

When you send through a clean signal, you measure A*B. When you get distortions, you know you’re only measuring B (because they are introduced after A). Then you derive A from that.

Re: Nam: Neural network emulator for guitar amplifiers

#13

Post by jononor »

earthnail wrote: post #11
Bad_CRC wrote: post #10

Earlier quoted context omitted.

With the Kemper Amp (a profiling amp) it goes through a series of "noises" to get a profile: https://www.youtube.com/watch?v=iL7tWFhH8E8 But yes, you get the sound of a specific EQ settings.

The Kemper amp is mathematically super elegant. Two matrices A and B, and one nonlinearity in between. That’s it. All the noise profiling does is figure out A and B, which correspond to the impulse response before and after the distortion. When you send through a clean signal, you measure A*B. When you get distortions, you know you’re only measuring B (because they are introduced after A). Then you derive A from that…

That is very interesting. So you have any resources to learn more about this approach to modelling?

Re: Nam: Neural network emulator for guitar amplifiers

#14

Post by klipklop »

TomWhitwell wrote: post #6
klipklop wrote: post #5

Earlier quoted context omitted.

NAM lets you essentially copy the sound/tone of a guitar pedal (no time based effects like reverb) or guitar amplifier. This means I can share a copy of my $3500 amp to people for free. Before this and a paid product called Tonex came out, it cost $1500+ to “profile”/copy digitally a guitar amp. The price floor for this stuff just became $0-400 depending on what solution you go with and what gear you have. This will…

Is it fair to say this clones a device with one specific set of knob positions? So if I want to clone a 5 knob fuzz pedal in every possible setting, that’s a lot of cloning to do? I may have misunderstood.

With the current state of the tech it’s best to do several captures with the various “sweet spots” a player is likely to use. You will often see files describe the gain or tone knob position or what channel was used on an amp.

It’s also not uncommon to create a capture with your pedal plugged into the amp as well. Popular for high gain heavy metal profiles to have a tube screamer in front of the amp. Stuff like the Kemper/Tonex/NAM work great with this kind of setup.

Re: Nam: Neural network emulator for guitar amplifiers

#15

Post by klipklop »

earthnail wrote: post #11
Bad_CRC wrote: post #10

Earlier quoted context omitted.

With the Kemper Amp (a profiling amp) it goes through a series of "noises" to get a profile: https://www.youtube.com/watch?v=iL7tWFhH8E8 But yes, you get the sound of a specific EQ settings.

The Kemper amp is mathematically super elegant. Two matrices A and B, and one nonlinearity in between. That’s it. All the noise profiling does is figure out A and B, which correspond to the impulse response before and after the distortion. When you send through a clean signal, you measure A*B. When you get distortions, you know you’re only measuring B (because they are introduced after A). Then you derive A from that…

Yeah the newer approach NAM used is much more accurate. Especially for high gain stuff. There are still some aliasing problems with NAM though. Even with that most would never hear about the difference of the real $3500 amp and the free NAM plug-in.

Playing feel on the other hand I guess is a different argument. Not sure if that is a placebo though. I do prefer the zero latency of all analog gear.

Re: Nam: Neural network emulator for guitar amplifiers

#16

Post by gizajob »

klipklop wrote: post #15
earthnail wrote: post #11

Earlier quoted context omitted.

The Kemper amp is mathematically super elegant. Two matrices A and B, and one nonlinearity in between. That’s it. All the noise profiling does is figure out A and B, which correspond to the impulse response before and after the distortion. When you send through a clean signal, you measure A*B. When you get distortions, you know you’re only measuring B (because they are introduced after A). Then you derive A from that…

Yeah the newer approach NAM used is much more accurate. Especially for high gain stuff. There are still some aliasing problems with NAM though. Even with that most would never hear about the difference of the real $3500 amp and the free NAM plug-in. Playing feel on the other hand I guess is a different argument. Not sure if that is a placebo though. I do prefer the zero latency of all analog gear.

I always think part of the ongoing use of valve amps is because of their transient response. It would be impossible to check in practice, but I think the transient latency is lower than solid state, because they're amplifying in a free field inside the tubes. I'm not sure how digital physical modelling and class-D power amplifiers is ever going to fully replicate this. The Kemper is naturally more convenient and feature-packed, but a valve amplifier will always do the one job that really counts, basically perfectly (until it breaks or catches fire).

Re: Nam: Neural network emulator for guitar amplifiers

#18

Post by pohl »

webprofusion wrote: post #9

This is cool, it's a little bit "batteries not included" so you need to get some Models for the amp part: https://github.com/pelennor2170/NAM_models and some Impulse Responses (IR files) for the cabinet emulation. When you put them together you can get some good results, maybe a little bit noisy. The important part is trying to develop a library of models for plugins to share and when paired with libraries of impulse…

That's very exciting. Some day a a mere mortal might be able to play a facsimile of a dozen slightly-different hand-made Dumbles.

One thing that this approach (and profiling) might not be able to do is what Ben Adrian's sound design team in Line 6 did, where they've come up with some delightful "amps" in the Helix that don't have real-world equivalents. For example, my favorite, the Ventoux, which he describes like this:

"The idea was to create a “coveted boutique amp” that had a different origin story. Most coveted boutique amps come from modified black panel fenders or modified marshall circuits. I wanted to do the same thing, but base it on the early 70s Orange circuits and the mid-wattage Fender Tweed circuits."

I'm not sure how one would to that with a NN approach.

Edit: now I'm wondering if one could make a large model trained by all the amplifiers, and have it dream up amps that don't exist.

Re: Nam: Neural network emulator for guitar amplifiers

#19

Post by Archit3ch »

ofalkaed wrote: post #8
TomWhitwell wrote: post #6

Earlier quoted context omitted.

Is it fair to say this clones a device with one specific set of knob positions? So if I want to clone a 5 knob fuzz pedal in every possible setting, that’s a lot of cloning to do? I may have misunderstood.

You understand correctly. All of the amp modeling and virtual analog stuff is still fairly limited and they largely focus on getting the stereotypical sounds of the source, not the full range. Modeling things more fully is not difficult but it is very processor intensive, many spice programs can do it quite well but are far from real time. So simple analog amp modelers like the sans-amp offerings still out perform th…

> I have been on again off again doing a fairly intensive write up on this topic going into all the technical details (primarily the hardware side) complete with a fairly full featured/accurate digital recreation of the original MiniMoog VCF in PureData but it is not exactly a priority and progress on that is rather slow.

I'd be very interested to see your approach. So far, the most promising (non-NN) technique I've seen requires taking a symbolic inverse of a sparse matrix, which is just barely possible for a simplified pedal model.

Re: Nam: Neural network emulator for guitar amplifiers

#20

Post by wintermutestwin »

pohl wrote: post #18
webprofusion wrote: post #9

This is cool, it's a little bit "batteries not included" so you need to get some Models for the amp part: https://github.com/pelennor2170/NAM_models and some Impulse Responses (IR files) for the cabinet emulation. When you put them together you can get some good results, maybe a little bit noisy. The important part is trying to develop a library of models for plugins to share and when paired with libraries of impulse…

That's very exciting. Some day a a mere mortal might be able to play a facsimile of a dozen slightly-different hand-made Dumbles. One thing that this approach (and profiling) might not be able to do is what Ben Adrian's sound design team in Line 6 did, where they've come up with some delightful "amps" in the Helix that don't have real-world equivalents. For example, my favorite, the Ventoux, which he describes like t…

>Some day a a mere mortal might be able to play a facsimile of a dozen slightly-different hand-made Dumbles.

Fractal's AxeFx has been able to do that for a long time. It has a couple different Dumbles and you can tweak the modeled circuitry in a myriad of ways because it is not a profiler, but rather it models the audio impact of each component that makes up the amp.

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