Recently I've been messing around with, and contributing to the Neural Amp Modeler project. It uses machine learning (more specifically the WaveNet model) to create captures of amplifiers and distortion pedals.
It has been gaining a lot of traction recently, with lots of people modeling their equipment. The resulting models are very good.
I've now got it integrated into my Raspberry Pi pedalboard. The audio for the above video was recorded on a Raspberry Pi 4.
The hardware on the pedalboard consists of:
- Raspberry Pi 4
- Hotone Jogg audio interface
- Hotone Ampero Control MIDI Controller
- Wio Terminal (used for a serial-based display)
My pedalboard is using a custom app on top of Jack audio, but I have also made a Neural Amp Modeler LV2 plugin available.
