[keyth72]

This project uses tensorflow/keras to emulate the sound of real guitar amplifiers and pedals on wav files. The model is trained on about three minutes of input/output guitar audio, and takes a few minutes to train. For example, you can record a $1000 amp and use this code to create a model to apply that sound to other wav files.

The purpose of this project is to improve on the previous WaveNet model built for the same task. Using LSTM is orders of magnitude faster and more accurate for emulating guitar signals than WaveNet. A real time guitar plugin exists for the WaveNet implementation, and a plugin for this the LSTM model is currently in work. Compare to Neural DSP’s Quad Cortex neural capture feature, which uses a similar technique on their $1600 floor modeler.