Stt/tts systems always seem to me so promising, but I pretty much never use voice to interface with a computer. Sometimes instead of typing on my phone, I use a voice dictation. I would be keen to use voice to control Claude code, but I've always felt that the way I speak is different from the way I write good prompts.
Fishing for anecdotes here, does anyone have any good tts/stt experiences?
I've always dreamed of having the ability to just talk to my computer (in the right circumstances) so I actually worked in the field for many years. The main reason I never use speech recognition today is because I have zero interest of sending recordings of my voice to the servers of some global corporations.
Running speech recognition and TTS locally is quite feasible, as projects like this one show.
If you want a local and open source option (MacOS only at the moment though), I've been happily using Keyscribe for dictation, which is built on Moonshine I believe.
https://rsperko.github.io/keyscribe/
> local and open source option (MacOS only)
ouch - this is ironic in an extreme, given Apple's OS layers and anti-GPL efforts
next, personal computers that come with a secret OS that can read all RAM by remote command?
I do a ton of coding (codex) with a tts/stt wrapper. During walks, cycling, in the car. Not every task is suited to this style of interaction, but many are. Long form codex replies are condensed, code blocks are suppressed all in the name of making it work for tts feedback. So it works best on well defined projects with guardrails, where you know the agent can perform well.
That's fantastic. I have long, winding trails near me also and one of these days I also want to start prompting a coding agent on my bike with a headset. Do you recommend any particular type of headset?
Edit: never mind, I see you already suggested the Shokz OpenComm2 in another comment. Thanks!
This is so alien to me. Why not plug into the machine matrix when out in the great outdoors enjoying sublime nature? Why not!
It's not a replacement for being outdoors, connecting with nature. It replaces indoor desk bound office work.
This is extremely dangerous and you should stop doing it.
https://etsc.eu/tiny-proportion-of-drivers-understand-danger...
Talking on the phone is extremely dangerous? What are your thoughts on talking with a passenger? Is that something that people ought to stop doing? Drive in silence. 100% focus?
Seems like an overreaction.
It's not my thoughts, it's simple facts.
All the studies show it's not an over-reaction, you're 400% more likely to have an accident. It is extremely dangerous and it's not an over-reaction, the more people do this, the more people die. It's simple maths. If you're doing extended programming sessions, you're not paying attention to the road like you should be.
And no, talking to a passenger is not as dangerous as it's a different cognitive load.
It'll take you 20 seconds to google this, please do and stop putting everyone else in jeopardy.
In what way is talking on the phone a different cognitive load that talking to a passenger?
After googling the 8th or 10th result had a link to the study I assume you are referencing.
I just don't agree with you. I believe that there is risk when driving inherently although relatively low and a 400% increase from 0.0001 to 0.0004 does not really concern me.
I have been in one accident in 15 years and I was not at fault and it was unavoidable.
Many people engage in all sorts of distracted driving, texting, eating, driving while tired etc. which I would wager are more detrimental than speaking on the phone.
Having your one bone to pick being speaking on the phone just seems absurd and an odd message to preach when nearly everyone does it.
I can't honestly think of a case where this would be remotely useful. This goes somehow beyond vibe coding to vibe interaction, where the only feedback comes via the AI. I'd love to see a concrete example of this working practice.
I've been building out the Android app that works as the wrapper between codex and me this way. ADB debugging access over WireGuard. I ask to add a local wake phrase detection for the phrase "Hey codex" to start dictation. Codex tells me it thinks Vosk or OpenWakeWord might be a good fit, I voice select Vosk. Codex starts working. Codex deploys (updates) the app on my phone and restarts it and I hear the task complete response. I say "Hey Codex" to test and ask for some tuning/improvements, or move onto the next task. All while keeping my phone in my pocket.
But there are countless projects I work on this way. Eg, I got an email from person X, it says it encountered a bug when doing x and y. Codex reads the email (using nvidia/gliner-PII to hide PII data) and investigates the reason for the bug and proposes a solution. I ask it to implement the fix on my dev server and increase test coverage. I enjoy my walk and after say 7 minutes get a an overview of the fix and can decide to deploy to production.
During cycling! Do you have a phone mount on your bike that you use while biking or is it all in-ear?
I have my phone in my pocket, no screen interaction is required. I use a headset (Shokz OpenComm2) with wind muff (when cycling). I made an Android app that listens for codex turn-complete or intermediate updates and plays them back to me. My answer is transcribed and pasted back to the relevant codex (tmux) session on the server (which I can select by voice) a tiny layer helps with things like /new, /plan, answer selection, etc.
I'd love to hear more about it!
I'm still wondering if this is something the big AI companies will come out with tomorrow, if it has business potential (it's extremely niche I think) or if I should put it on GitHub and build a community around it. This is what the Android app looks like: https://imgur.com/a/qy8B2gt https://imgur.com/a/C0eTPyn
... I cannot think of an activity less suitable for coding (except scuba diving)
I would die In minutes
Think long winding, quiet, dedicated cycling roads in forested areas and natural parks. Not busy roads shared with cars and lorries.
I use the Hex[1] app on MacOs for near instant transcription with Parakeet V3. This is how I speak to Code agents at least 80% of the time. The idea is - I tend to be lazy if I need to type lots of details, so speaking lets me get into details that I otherwise wouldn’t and this helps give more useful context to the agent. This often tends to be an unstructured brain dump so I sometimes ask the agent to repeat back what it understood, so I can make sure, and this also likely helps it stay on track.
[1] hex https://github.com/kitlangton/Hex
I used to use Handy but as of a few months ago it had stuttering and other issues so I switched to Hex. Even for relatively long minute long dictation, transcription is near instant and accuracy is more than sufficient, especially when talking to AI since it that can “read between the lines “.
Using voice with code agents is a huge unlock and I’m surprised to see some people I recommend it to, still resist it.
As for TTS I found it fun to make a voice plugin for Claude Code that uses PocketTTS, so it can give brief updates whenever it finishes a turn:
https://pchalasani.github.io/claude-code-tools/plugins-detai...
I (well CC and I) wrote a tts/stt pipeline for the CLI of CC. It's a lot more, immersive I guess, when I open my dev environment and it gives me a verbal walk through of what's going on.
(this inspired some more demo-y stuff I have where claude can manipulate the mouse and audit things it's built visually in conjunction with that). I'm sure this has already been wrapped up into some MCP framework, but it was fun to build it super early on and it just sort of works for me.
I don't use this in my day job, but it does feel very futuristic when I pull up my home lab.
I'm founder of ottex.ai, I use stt pretty much all the time when work with AI and quite often for communications to draft emails and chat messages.
I started ottex half a year ago after I tested gemini 2.5 flash native audio support. I was blown away by the quality of transcripts and decided to built an app to use it myself.
Currently the default model in the app is Gemini 3 flash, but you can connect to 9 providers and God knows how many models to play with.
I would suggest you to try this models for ai prompting:
- Gemini 3 / 3.5 flash - Soniox rtt v5 - Mistral transcribe v2 - assembly 3.5 pro
What I want is a 1940s style “taking dictation” where the words I say go through a step where the goal is to create the text Im imagining. So if I say “… very significant, actually just significant…” what Claude Code receives is “…significant…”.
I built this myself with whisper -> “secretary” prompt -> Claude Code, but having the first two steps be interactive is really what I would want.
I use dictation to drive Claude code frequently, and it’s never had a problem with stream of consciousness and retroactive correction. Maybe try just direct voice and see if you notice any difference versus pre-cleaning?
Claude Code's speech recognition works so well for me, I was blown away the first time I tried it. I wish I knew what model they were using (I assume it's not in house since they've never talked about it).
I acknowledge this may just mean I haven't tried enough modern voice recognition systems. But I've used Whisper and I don't think it works nearly as well for real-time speech.
(I still don't tend to use voice mode in Claude Code because I find typing more comfortable.)
On some days, half of my promts to Copilot at work are spoken to a local whisper medium model running on an Intel ARC GPU.
One of my side projects is a tool that lets you control your entire system with STT. It's built on Whisper and supports hot swapping custom profiles, so you can add easy commands for any software.
I intend to use it to work on low stakes vibe coding projects while I'm doing other stuff. Todays LLMs are a lot better at interpreting rambling dictation with mid-message corrections.
There are a few paid programs out there that do the same, but they made my vibe slop sense tingle and are not aimed at development.
https://handy.computer is the goto. It can even add an LLM pass (optionally) so if you say "remind me to buy three, actually, four, eggs" it'll type "remind me to buy four eggs".
Industry leading Interactive Voice Response systems have become very good at filling in ambiguous information from context, and modulating pronunciation to Ape emotional information.
However, being able to interact with these natural language systems in uncontrolled settings is still a fools errand. For STT, there is also regional dialect, slang, and individual differences.
Witnessing blind users hit unrecognizable reading-speeds on old Gordon 8 TTS systems was surprising. I learned people adapt to imperfect systems pretty quickly. =3
For STT, wispr flow has a generous free tier. For TTS, I have Claude read out loud what it just finished as a stop hook, so I know which claude finished up.
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