After two months of pause, we're preparing to release new Getting Simple podcast episodes.
Editing and publishing add friction and delays to my process, so I'm exploring code and ML workflows to post-process of episodes' audio and generate transcripts, summaries & notes.
I'm not there yet. But OpenAI's Whisper (free) and Descript (paid) already provide accurate transcriptions. Existing projects and companies use #GPT-like language models to extract episode keywords, topics, chapters & summaries.
We'll soon have automatic episode notes.
It's exciting. I think we're getting very, very close.
I've also played with Spotify's
pedalboard Python package to post-process audio without relying on a Digital Audio Workstation (DAW).
That's cool because I can create reusable scripts for specific recording conditions and forget about audio editing — say, compressing, limiting, applying noise gates, or normalization—things you'd otherwise do in Adobe Audition.
Let me know if you'd like to see these automations in the live stream and video tutorials or shared here on Twitter at @nonoesp.