Deep Learning for Guitar Effect Emulation
61–70 of 168 posts
Re: Deep Learning for Guitar Effect Emulation
#62Pretty 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.
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 as being very interesting.
Re: Deep Learning for Guitar Effect Emulation
#63Pretty 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".
Re: Deep Learning for Guitar Effect Emulation
#64Earlier 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…
Re: Deep Learning for Guitar Effect Emulation
#65Earlier quoted context omitted.
You're right in the "this is one more tool in the belt" sense but there are modelers like the Kemper and Fractal already out there that make your guitar sound like... anyone... and they are really convincing. I'd argue this is almost a solved problem. Still cool, nonetheless.
Building the model is not solved though. Kemper sort of does that by not sure what, but an approach that simply measures the effect and creates a complete model in hours would radically change the industry. Companies like Yamaha (line6) would be able to add hundreds of simulations in months instead of a couple.
An acquaintance that builds boutique studio gear had some of his creation modeled by them, and we were quite impressed.
Re: Deep Learning for Guitar Effect Emulation
#66Truly 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 a nostalgia factor and tweaking dials is cool. As a computer guy though, I much prefer the ability to make things like this in my bedroom: https://i.imgur.com/OqMoBxz.png And when I want to tweak a dial, I program an expression foot controller to tweak any parameter (or multiple).
All that said, great to be looking at modelling techniques...
Re: Deep Learning for Guitar Effect Emulation
#67> 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.
Re: Deep Learning for Guitar Effect Emulation
#68Earlier quoted context omitted.
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?
Re: Deep Learning for Guitar Effect Emulation
#69> 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.
Very impressive given it's from a NN, but I specifically moved to analog for that reason.
Re: Deep Learning for Guitar Effect Emulation
#70"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…
You will have the same sound from gig to gig and a lot of band really value this.