I’ve helped thousands learn tmux through my free resource under the name The Tao of tmux, which I kept as part of the documentation for the tmuxp session manager. And now, it’s been expanded into a full-blown book with refined graphics, examples, and much more.
Since the 1940s, electric guitarists, keyboardists, and other instrumentalists have been using effects pedals, devices that modify the sound of the original audio source. Typical effects include distortion, compression, chorus, reverb, and delay. Early effects pedals consisted of basic analog circuits, often along with vacuum tubes, which were later replaced with transistors. Although many pedals today apply effects digitally with modern signal processing techniques, many purists argue that the sound of analog pedals can not be replaced by their digital counterparts. We’ll follow a deep learning approach to see if we can use machine learning to replicate the sound of an iconic analog effect pedal, the Ibanez Tube Screamer. This post will be mostly a reproduction of the work done by Alec Wright et al. in Real-Time Guitar Amplifier Emulation with Deep Learning1. Alec Wright et al., “Real-Time Guitar Amplifier Emulation with ↩