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)
This is cool! Would you be willing to post a build list and instructions?
ReplyDeleteDid you write custom software to show the signal chain on the display?
I updated the post with the hardware used. Software is a custom app running on top of Jack audio.
DeleteThank you, is Jack Audio running on top of Windows or another OS?
DeleteAnything else I should know before trying out myself?
It's running on a Raspberry Pi - so Linux.
Delete