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Deep Learning for Guitar Effect Emulation

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Re: Deep Learning for Guitar Effect Emulation

#141

Post by qppo »

nil-sec wrote: post #139
qppo wrote: post #99

Earlier quoted context omitted.

I know of a few shops that took VC money. The big problem isn't the market size so much as how slow the market moves. The product lifetime of a plugin is around a decade. And users hate subscriptions. And it's really hard to determine the value you add to your customers. And no one wants to pay you. It's basically a terrible place to be a developer in it for the money. Really fun work otherwise. The cool gigs are the…

The success of splice would disagree with your notion that “users hate subscriptions”. Given the horrendous price point of many of these plugins it seems to be perfect for a subscription based model. To me it always seemed there is more of a pushback from the industry producing vsts than from the consumers.

Splice's numbers aren't public so I can't comment on their success. Avid's are, and they had a terrible quarter - and they're the poster child (alongside Adobe) for subscription licensing in creative software. But I'd be interested to see what the breakdown in revenue is for plugin licenses versus preset/sample packs (bit of a blade & razor model there).

The price points really aren't horrendous if you consider how expensive the engineering is, how little demand there is, and how long you need to maintain a product. You aren't being ripped off by spending a couple hundred bucks on a plugin. I think we'll end up at a place where everything is a subscription, but I can tell you from experience that it creates friction for the users.

Re: Deep Learning for Guitar Effect Emulation

#142

Post by munificent »

samplenoise wrote: post #111
munificent wrote: post #102

I'm not an expert on machine learning or DSP, but I do know just enough of each to suspect this isn't anywhere near as impressive as it seems. A distortion pedal is essentially just a waveshaper [1]. Think of audio in digital terms as just a series of numbers. A waveshaper is just a simple mathematical function. To apply it, you literally just apply the function to each value in the input stream and there's your outp…

> You could accomplish much the same by using a "depth-1 network" and running an impulse through it This would be true for a linear impulse response, however for this kind of effects you need both state/memory (like a convolution) and non-linearity (like a waveshaper), which is why people use RNN's and CNN's

Ah, good point. Thank you for mentioning non-linearity. This has helped clarify my novice thinking on this.

Re: Deep Learning for Guitar Effect Emulation

#143

Post by munificent »

melq wrote: post #126
munificent wrote: post #95

Earlier quoted context omitted.

If you drop an audio buffer and fire off a 22kHz impulse into a 50,000 watt soundsystem, you are going to have thousands of very unhappy people and likely some hearing damage.

Point taken, but 22khz is too high for people to hear I think.

You don't need to perceive a sound to have your ears be damaged by it.

(This goes in both directions on the spectrum too. You can have your hearing damaged by infrasound as well.)

Re: Deep Learning for Guitar Effect Emulation

#144

Post by TheRealPomax »

kleer001 wrote: post #140
TheRealPomax wrote: post #75

Earlier quoted context omitted.

That implication would be wildly incorrect.

With the operative word being "developers" I disagree.

Yeah but facts don't really care about agreement: there are loads of renowned single-person VST shops, and many more "just a handful of folks" ones. Chris Heinz, Steve Duda, Strezov Sampling, Matt Tytel, heck even Plugin Guru, etc. etc. are all renowned folks in the VST/VSTi world, and that doesn't even scratch the surface.

Re: Deep Learning for Guitar Effect Emulation

#145

Post by strbean »

NobodyNada wrote: post #116
avisser wrote: post #109

Earlier quoted context omitted.

For guitar pedals, there is an implied sub-perceptibility. The output needs to happen as I play - if the delay is too long, it's now a delay pedal. So realtime might match your definition, but it is consistent in audio production. For humans, you can start to notice the lag @ 50ms. (A selection of experimental results summarized here https://gamedev.stackexchange.com/a/74975 )

Latency is much more noticeable when you’re playing a musical instrument; 25-30ms is the point at which it becomes distracting in my (anecdotal) experience as a keyboardist. 50ms would be literally unplayable —- I cannot keep in time if latency is that severe. And that’s total output latency from the moment a key is depressed to the moment the sound comes out the speakers, so it’s important for every component in the…

Throw on some headphones, and mix your clean signal with the rest of the ensemble on a 50ms delay.

(jk)

Re: Deep Learning for Guitar Effect Emulation

#146

Post by nil-sec »

qppo wrote: post #141
nil-sec wrote: post #139

Earlier quoted context omitted.

The success of splice would disagree with your notion that “users hate subscriptions”. Given the horrendous price point of many of these plugins it seems to be perfect for a subscription based model. To me it always seemed there is more of a pushback from the industry producing vsts than from the consumers.

Splice's numbers aren't public so I can't comment on their success. Avid's are, and they had a terrible quarter - and they're the poster child (alongside Adobe) for subscription licensing in creative software. But I'd be interested to see what the breakdown in revenue is for plugin licenses versus preset/sample packs (bit of a blade & razor model there). The price points really aren't horrendous if you consider how e…

Agreed. The business model seems to be to give access to the rent to own deals via the sample subscription fee. Don’t think they make any money of their plugin deals. I’m also not arguing it’s too expensive or a rip off. But it’s still a large amount of money for software, in the private space at least. The rent to own thing seems like a smart tool to get rid of the barrier of entry.

Re: Deep Learning for Guitar Effect Emulation

#147

Post by melq »

hashkb wrote: post #137
wintermutestwin wrote: post #92

Earlier quoted context omitted.

I guess you are technically right, but this part of the discussion is highly subjective. I was merely pointing out that the quoted statement was subjective and I wasn't using "hipster" as a pejorative - I was actually being somewhat sympathetic to their view. Overall, my goal was to add to this discussion by pointing out the massive progress that has been made and also to show off my supercool signal path in the hope…

It would have gone over better with me (your average analog hipster) if you'd just mentioned the positive aspects of the thing you like. I'm eagerly awaiting the day when modeling is actually good enough for me; and your (common) attitude (that it is, obviously, and anyone who can't hear it is nostalgic/supersitious/hipster) is one of the reasons I don't give modelers a try more often.

It wasn't an ad hominem attack. Ad hominem quite literally refers to an attack against a specific person. Not only was he not attacking a person, but referring to 'hipsters' is not necessarily pejorative.

I believe he was incorrect to call guitar players who use analog equipment hipsters, as using analog equipment is the status quo, not some niche subculture outside of the mainstream.

I would like to respectfully suggest being a little less sensitive, though. Not giving new things a chance because of other people attitudes seems very silly to me.

Re: Deep Learning for Guitar Effect Emulation

#148

Post by afro88 »

munificent wrote: post #102

I'm not an expert on machine learning or DSP, but I do know just enough of each to suspect this isn't anywhere near as impressive as it seems. A distortion pedal is essentially just a waveshaper [1]. Think of audio in digital terms as just a series of numbers. A waveshaper is just a simple mathematical function. To apply it, you literally just apply the function to each value in the input stream and there's your outp…

I think you're hand waving away all the complexity. You're right that distortion is pretty much waveshaping. But all the nuance, "warmth" and lovely non-linearities that make these pedals highly sought after is the really really hard part. It can't be simply solved with convolution.

The same pedal from this post has been pain stakingly circuit modeled by Cytomic[1] over the past few years and still isn't out of beta. Analog circuit modeling is a huge thing in DSP right now because it's the closest we have to proper 1:1 software clones of analog hardware. But it's incredibly time consuming.

I'm really excited by this use of WaveNet. It could drastically cut down the time to clone old costly to maintain hardware. But it will have some way to go before you can tweak the parameters in realtime. Or so I assume?

[1]: https://cytomic.com/#plugins

Re: Deep Learning for Guitar Effect Emulation

#149

Post by melq »

munificent wrote: post #143
melq wrote: post #126

Earlier quoted context omitted.

Point taken, but 22khz is too high for people to hear I think.

You don't need to perceive a sound to have your ears be damaged by it. (This goes in both directions on the spectrum too. You can have your hearing damaged by infrasound as well.)

Ah, this makes a lot of sense, thank you. Much like there are spectrums of light we can't see that can damage the eyes.

Re: Deep Learning for Guitar Effect Emulation

#150

Post by williamdclt »

gregsadetsky wrote: post #62
whiddershins wrote: post #39

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.

I was in talks with a (new-style) 'label' that sells samples, sound packs, and VST plugins. Some of their plugins have been purchased 25k times. One of the things I've also heard from labels is that not only there's money in the VST world (it's also very crowded, piracy is rampant as noted, etc.), a lot of plugins are ported over to iOS and are sold as "virtual pedals". The number of sales and revenue there was noted…

When I had an active band, our guitarist went from bringing his amp to rehearsal, to having a bunch of pedals, to having a digital pedal board, to having an iPhone with some sort of tiny adapter.

I made fun of him and we wouldn't have trusted it to be used live, but damn it worked impressively well

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