About this episode
Our Audio Intelligence Lab built the world’s beefiest effects pedal using machine learning and Python. Say hello to Pedalboard, an open source framework for adding studio-quality effects to audio files — at a speed and scale well beyond the capabilities of the tools you’d normally find in a music studio.
Host and principal engineer Dave Zolotusky talks with Peter Sobot (@psobot — not a robot?), one of the ML engineers on the team that built Pedalboard. They discuss the world of audio effects processing in both music and ML research, how we use Pedalboard in our own research, Python as ML glue (with some secret C++ under the hood), and the unexpected use cases that appear whenever you open source your software.
Plus, a live programming demo…on a podcast? “Tap, tap, tap, return…”? How interesting can that be? Listen to find out!
Learn more about Pedalboard, open source, and ML and audio research at Spotify:
Read about Pedalboard on our blog
Pedalboard on GitHub
Spotify’s Audio Intelligence Lab
Spotify open source projects on GitHub
More open source stories
Read what else we’re nerding out about on the Spotify Engineering Blog: engineering.atspotify.com
You should follow us on Twitter @SpotifyEng and on LinkedIn!
