Live data from Hacker News

Deep Learning for Guitar Effect Emulation

teddykoker.com

41–50 of 168 posts

Re: Deep Learning for Guitar Effect Emulation

#41
post #16

Earlier quoted context omitted.

Implementing a VST plugin is literally the exact definition of requiring strict latency guarantees. Your comment winds through a lot of unrelated comparisons to ultimately not make any sense. “Usually fast enough” are three words that guarantee failure in a live show/MIDI environment, which is a large use case of VST and its peers beyond production. By extension, “usually fast enough” further guarantees nobody will e…

"Usually fast enough" is unfortunately the only guarantee a preemptive multitasking OS can give you. Unless your system is guaranteeing your program x cycles of uninterrupted processing per frame of audio and you can consistently process the frame in that amount of cycles, the only mitigation is to deliver frames in large enough chunks that you never run out of time in practice under agreeable circumstances. That sai…

It is completely irrelevant, given the context. The only, only, only thing real-time means here is “can be run on a live signal passing through it” rather than “is a slow, offline effect for a DAW”. No hard real-time, no soft real-time, no QNX, no pulling out the college compsci textbook. There IS real-time in that sense in DSP, it just isn’t in a VST plugin.

I’ll repeat again that any compsci theorycrafting is not the concern here, and real-time has a very specific meaning in DSP. Computer science does not own the concept of real-time, and the only people tripping over the terminology are those with more compsci experience than DSP. I appreciate everyone trying to explain this to me, but (a) I understand both, and (b) this is like saying “no, Captain, a vector could mean anything like a mathematical collection, air traffic control should learn a thing or two from mathematics.”

Re: Deep Learning for Guitar Effect Emulation

#43
post #14

Earlier quoted context omitted.

Reverb is time invariant? You can set custom decay time, rate etc, so the one not can be heard for say, 10 seconds if you want to go full Devin Townsend. I'd think Chorus would work better. I wanted to do a very similar project, but with an overdrive. Let's see if I get time anytime soon!

>Reverb is time invariant? You might want to familiarize yourself with [0]. Time-invariance is a specific property of a system, where the output (for any given input) has no dependency on if the input signal happens now or 1 second from now or 100 years from now (except for the corresponding delay). Most reverb models are, to a first approximation, time invariant, because the effect will have the same sound for the s…

Thanks for the info! Did some reading and I can see plain reverb being time invariant indeed :) I never realised chorus pedals did more than just stack frequency offsets onto your signal, but I only really play distorted so choruses are of limited use to me.

Pasting the other response below as well:

> Ah righto, the reverb pedal I'm most familiar with turns out to not be just reverb - EQD Afterneath does a whole bunch of funky stuff. Plain reverb though, yeah. I was approaching this more from the angle of training a neural network, where the input and output waves have to be correlated over a great span of time/ samples.

Re: Deep Learning for Guitar Effect Emulation

#44
post #34
post #29

Earlier quoted context omitted.

The show won't collapse, if you have one glitch an hour.

Yes, it absolutely 100% will, depending on what you mean by handwaving “glitch”. VST is built into chains, and a flaky plugin will derail an entire performance, often making downstream plugins crash. I’m speaking from extensive experience writing plugins and performing with them in multiple hosts and trigger setups. It’s not a robust protocol, but it gets the job done. Are you speaking from some experience with which…

Agreed. If anyone wants to see some of the more successful DSP work being done today for pro or prosumer audio, I recommend checking out Strymon and Universal Audio products. Both make use of SHARC SoCs and achieve great results.

Re: Deep Learning for Guitar Effect Emulation

#45
post #34
post #29

Earlier quoted context omitted.

The show won't collapse, if you have one glitch an hour.

Yes, it absolutely 100% will, depending on what you mean by handwaving “glitch”. VST is built into chains, and a flaky plugin will derail an entire performance, often making downstream plugins crash. I’m speaking from extensive experience writing plugins and performing with them in multiple hosts and trigger setups. It’s not a robust protocol, but it gets the job done. Are you speaking from some experience with which…

A VST that doesn't fill its buffer on time shouldn't crash another plugin. It's your other plugins that are flaky.

Re: Deep Learning for Guitar Effect Emulation

#46
post #34
post #29

Earlier quoted context omitted.

The show won't collapse, if you have one glitch an hour.

Yes, it absolutely 100% will, depending on what you mean by handwaving “glitch”. VST is built into chains, and a flaky plugin will derail an entire performance, often making downstream plugins crash. I’m speaking from extensive experience writing plugins and performing with them in multiple hosts and trigger setups. It’s not a robust protocol, but it gets the job done. Are you speaking from some experience with which…

Are there any VST containers? Something that will wrap the VST, intercept under-runs or other bad behaviour and substitute some alternative signal (zero, passthrough, etc.). This could also be part of the host software.

The article and your comments inspired in me the idea of a wave-net based VST learning wrapper. If the real plugin fails, substitute a wave-net based simulation of the plugin.

Re: Deep Learning for Guitar Effect Emulation

#47
post #34

Earlier quoted context omitted.

Yes, it absolutely 100% will, depending on what you mean by handwaving “glitch”. VST is built into chains, and a flaky plugin will derail an entire performance, often making downstream plugins crash. I’m speaking from extensive experience writing plugins and performing with them in multiple hosts and trigger setups. It’s not a robust protocol, but it gets the job done. Are you speaking from some experience with which…

A VST that doesn't fill its buffer on time shouldn't crash another plugin. It's your other plugins that are flaky.

[deleted]

Re: Deep Learning for Guitar Effect Emulation

#48
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.

There are definitely big players making a lot of money from plugins they develop. Here are a few to check out:

($1200) https://www.native-instruments.com/en/products/komplete/bund...

($300) https://www.soundtoys.com/product/soundtoys-5/

($500) https://www.arturia.com/products/analog-classics/v-collectio...

However, piracy is also pretty big when it comes to plugins.

Re: Deep Learning for Guitar Effect Emulation

#49
A neat approach for sure. I am more interested in SPICE style modeled VSTs though. There's no need to throw ML at a simple math problem to get a bad approximation. I have not found many VSTs that seem like they're doing proper simulation of analog circuits. The VST space is filled with people claiming awesome results, but never revealing the sauce. If you're making a convincing sounding zener limiter, what are you actually doing? There are a dozen different levels of approximations you could make. Shouldn't a VST that is really simulating the analog circuit advertise that? On paper it should be easy, right? I've sat down with pen and paper to try to write out a simple input/output equation for a zener limiter circuit and I decided it was probably more worth my time to just plop a zener SPICE model into some language that could evaluate expressions and compile to VST (or use a systems of equations solver).

And then there's the real holy grail of analog simulation: the tube amplifier. I'm not sure SPICE models really capture the limiting behavior of tubes very well. You might need to implement the spec sheet in code. All fun sounding problems, and I'm not sure anyone has even done them yet.

Re: Deep Learning for Guitar Effect Emulation

#50
post #48

Earlier quoted context omitted.

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.

There are definitely big players making a lot of money from plugins they develop. Here are a few to check out: ($1200) https://www.native-instruments.com/en/products/komplete/bund... ($300) https://www.soundtoys.com/product/soundtoys-5/ ($500) https://www.arturia.com/products/analog-classics/v-collectio... However, piracy is also pretty big when it comes to plugins.

Sure, but,

>Do solo or small shop vst plugin developers make any money?

Post reply on HN