Talking to machines or how i created whisper-talk

I created a tool that helps me braindump my ideas faster

aljaz

17. Januar 2026January 17, 2026 · 3 Min. Lesezeit3 min read

(in case you just want the github link without reading the hallucinations of my neural network - here you go)

I hate voice memos. Mostly I hate to receive them. You can’t quickly glance over to remember the content of the conversation, the key piece of information you need is hidden in a 3minute voice note. But I recently learned that talking to machines is quite practical.

I even tweeted (its forever gonna be tweeting) about talking to an LLM while pooping. Not that I haven’t used the feature before a few times but I never got the hang of it because I like to brain dump but then I want to read the reply (my brain works funny). I’ve even created a bot a while back that would transcribe signal voice memos that I braindumped to it, but it didn’t stick, Until I’ve come across hyprwhspr about a week or two ago. I immediately liked the idea, I’ve done several whisper projects in the past, whisper-rs-cli just this week so I dug into it. I wanted it as lean as possible so I first created a stripped down fork of it and fitted it to my fedora/ubuntu setup. But it was somewhat slowish in python and I’ve just came out of doing whisper-rs-cli so the decision was obvious. I need a rust version. Given that I had a working python version that I liked I thought its gonna be a slightly more straightforward path. It wasn’t. Specially when I went down the path of “lets add real time typing into any app just for giggles” path. Since I’ve done some real(ish) time transcription api experiments before I thought that will also just be an extra half an hour.

Narrator: it wasn’t.

In the end I realized that I don’t really WANT that functionality, I just thought it will look cooler in the README so saner thoughts prevailed, I pushed the code to a branch in case I want to procrastinate at some later time and viola, we’re back at actually working version of the thing that I wanted. Which is whisper-talk.

Pure simplicity:

I’ve been using the python version of it for couple days and it became an almost natural part of my workflow already. I mostly use it for writing prompts, and given how much of them I write my fingers are very happy about it.

original: https://disobey.dev/posts/talking-to-machines-or-how-i-created-whisper-talk/

#ai#voice#whisper

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