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Posted (edited)

The short answer is, it depends. Sound is subjective, and to my ears, I can hear the difference if I lower the parameters for high gain targets. The less distorted the sound, the easier it is to train, so for clean or low distortion I might get away with lowering the parameters.  But I want it to work as well as it can for any potential sound, so it’s my best guess based on limited testing on the hardware I have available.  User feedback on what works and what doesn’t has helped a lot!  
 

With the  training, you’re trying to minimize loss, which is the difference between the predicted sound and the actual sound, so I can put a number value on the accuracy of the models. I also look at plots of the waveforms to visually see how close the sound is.

Edited by Keith Bloemer
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Posted

So, if I set up a double blind or ABX test, can you reliably tell which is which 100% of the time?

I'm concerned that modern plugins often talk too much about realistic sounding as a justification to not make optimizations and you cannot hear any difference in most cases unless you are looking at each example. Or specific minutia of how a piece of gear operates is modeled sacrificing performance, even though that detail doesn't matter in practice.

  • Like 1
Posted

Good arguments, I’m guessing you mean can I tell the difference between a large model and a slightly smaller model? Probably not for every case. The tricky thing about plugins is you have to generalize them to work well on the most hardware/OS/DAWs. Where things like Kemper and Quad Cortex have full control because they own the hardware too. If I start selling plugins these are things I definitely want to think about. But for now I just made something interesting that I enjoy using, and decided to open source it because it turns out there’s a lot of smart people that want to help improve it. Sometimes it’s hard to separate the software aspect from the music, but you bring up a good point that the music and sound should come first before fancy technology.

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