Show HN: Whispering – Open-source, local-first dictation you can trust (github.com)

591 points by braden-w ↗ HN
Hey HN! Braden here, creator of Whispering, an open-source speech-to-text app.

I really like dictation. For years, I relied on transcription tools that were almost good, but they were all closed-source. Even a lot of them that claimed to be “local” or “on-device” were still black boxes that left me wondering where my audio really went.

So I built Whispering. It’s open-source, local-first, and most importantly, transparent with your data. Your data is stored locally on your device, and your audio goes directly from your machine to a local provider (Whisper C++, Speaches, etc.) or your chosen cloud provider (Groq, OpenAI, ElevenLabs, etc.). For me, the features were good enough that I left my paid tools behind (I used Superwhisper and Wispr Flow before).

Productivity apps should be open-source and transparent with your data, but they also need to match the UX of paid, closed-software alternatives. I hope Whispering is near that point. I use it for several hours a day, from coding to thinking out loud while carrying pizza boxes back from the office.

Here’s an overview: https://www.youtube.com/watch?v=1jYgBMrfVZs, and here’s how I personally am using it with Claude Code these days: https://www.youtube.com/watch?v=tpix588SeiQ.

There are plenty of transcription apps out there, but I hope Whispering adds some extra competition from the OSS ecosystem (one of my other OSS favorites is Handy https://github.com/cjpais/Handy). Whispering has a few tricks up its sleeve, like a voice-activated mode for hands-free operation (no button holding), and customizable AI transformations with any prompt/model.

Whispering used to be in my personal GH repo, but I recently moved it as part of a larger project called Epicenter (https://github.com/epicenter-so/epicenter), which I should explain a bit...

I’m basically obsessed with local-first open-source software. I think there should be an open-source, local-first version of every app, and I would like them all to work together. The idea of Epicenter is to store your data in a folder of plaintext and SQLite, and build a suite of interoperable, local-first tools on top of this shared memory. Everything is totally transparent, so you can trust it.

Whispering is the first app in this effort. It’s not there yet regarding memory, but it’s getting there. I’ll probably write more about the bigger picture soon, but mainly I just want to make software and let it speak for itself (no pun intended in this case!), so this is my Show HN for now.

I just finished college and was about to move back with my parents and work on this instead of getting a job…and then I somehow got into YC. So my current plan is to cover my living expenses and use the YC funding to support maintainers, our dependencies, and people working on their own open-source local-first projects. More on that soon.

Would love your feedback, ideas, and roasts. If you would like to support the project, star it on GitHub here (https://github.com/epicenter-so/epicenter) and join the Discord here (https://go.epicenter.so/discord). Everything’s MIT licensed, so fork it, break it, ship your own version, copy whatever you want!

58 comments

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Cool! I just started becoming interested in local transcription myself.

If you add Deepgram listen API compatibility, you can do live transcription via either Deepgram (duh) or OWhisper: https://news.ycombinator.com/item?id=44901853

(I haven’t gotten the Deepgram JS SDK working with it yet, currently awaiting a response by the maintainers)

Great work! I've been using Willow Voice but I think I will migrate to this (much cheaper) but they do have a great UI or UX just by hitting a key to start recording and the context goes into whatever text input you want. I haven't installed whispering yet but will do so. P.S
Does Whispering support semantic correction? I was unable to find confirmation while doing a quick search.
I’ve been using whispering for about a year now, it has really changed how I interact with the computer. I make sure to buy mice or keyboards that have programmable hotkeys so that I can use the shortcuts for whispering. I can’t go back to regular typing at this point, just feels super inefficient. Thanks again for all your hard work!
This is wonderful, thank you for sharing!

Do you have any sense of whether this type of model would work with children's speech? There are plenty of educational applications that would value a privacy-first locally deployed model. But, my understanding is that Whisper performs pretty poorly with younger speakers.

Now we just need text to speech so we can truly interact with our computers hands free.
Does this support using the Parakeet model locally? I'm a MacWhisper user and I find that Parakeet is way better and faster than Whisper for on-device transcription. I've been using push-to-transcribe with MacWhisper through Parakeet for a while now and it's quite magical.
Windows Defender says it is infected.
am I not getting it correctly; it says local is possible but can't find any information about how to run it without any api key?

I get the whispers models, and do what? how to run in a device without internet, no documentation about it...

are there any non-Whisper-based voice models/tech/APIs?
How does this compare to VoiceInk which is also open-source and been there much longer and supports all the features that you have? https://github.com/Beingpax/VoiceInk
VoiceInk (one time payment) and WisprFlow (subscription) are currently my fav dictation apps. I just looked at Whispering and have to say VoiceInk is far superior to Whispering in terms of Ux, and clarity of settings, so I think VoiceInk deserves at least as much attention. There are several things that make a huge difference things that make a huge difference in dictation apps, besides the obvious speed and accuracy:

- allow flexible recording toggle shortcuts - show a visual icon with waves etc showing recording - how the clipboard is handled during recording (does it copy to clipboard? does it clear it after text output?)

VoiceInk is nearly there in terms of good behavior on these dimensions, and I hope to ditch my Wispr Flow sub soon.

> "I think there should be an open-source, local-first version of every app, and I would like them all to work together. The idea of Epicenter is to store your data in a folder of plaintext and SQLite, and build a suite of interoperable, local-first tools on top of this shared memory. Everything is totally transparent, so you can trust it."

Yes! This. I have almost no experience w/ tts, but if/when I explore the space, I'll start w/ Whispering -- because of Epicenter. Starred the repo, and will give some thought to other apps that might make sense to contribute there. Bravo, thanks for publishing these and sharing, and congrats on getting into YC! :)

> I’m basically obsessed with local-first open-source software.

We all should be.

All these all just Whisper wrappers? I don't get it, the underlying model still isn't as good as paid custom models from companies, is there an actual open source / weights alternative to Whisper for speech to text? I know only of Parakeet.
I've been interested in a tool like this for a while. I currently have tried whisprflow and aqua voice but wanted to use my API key and store more context locally. How does all the data get stored and how can I access it?
Looks like a really cool project. Do you have any opinions on which transcription models are the best, from a quality perspective? I have heard a lot of mixed opinions on this. Curious what you've found in your development process?
Wait, I'm confused. The text here says all data remains on device and emphasises how much you can trust that, that you're obsessed with local-first software, etc. Clicking on the demo video, step one is... configuring access tokens for external services? Are the services shown at 0:21 (Groq, OpenAI, Antrophic, Google, ElevenLabs) doing the actual transcription, listening to everything I say, and is only the resulting text that they give us subject to "it all stays on your device"? Because that's not at all what I expected after reading this description
Not a fan of high resource use or reliance on proprietary vendors/services. DeepSpeech/Vosk were pre-AI and still worked well on local devices, but they were a huge pain to set up and use. Anyone have better versions of those? Looks like one successor was Coqui STT, which then evolved into Coqui TTS which seems still maintained. Kaldi seems older but also still maintained.

edit: nvm, this overview explains the different options: https://www.gladia.io/blog/best-open-source-speech-to-text-m... and https://www.gladia.io/blog/thinking-of-using-open-source-whi...

Thanks for sharing! Transcription suddenly became useful to me when LLMs started being able to generate somewhat useful code from natural language. (I don't think anybody wants to dictate code.) Now my workflow is similar to yours.

I have mixed feelings about OS-integration. I'm currently working on a project to use a foot-pedal for push-to-transcribe - it speaks USB-HID so it works anywhere without software, and it doesn't clobber my clipboard. That said, an app like yours really opens up some cool possibilities! For example, in a keyboard-emulation strategy like mine, I can't easily adjust the text prompt/hint for the transcription model.

With an application running on the host though, you can inject relevant context/prompts/hints (either for transcription, or during your post-transformations). These might be provided intentionally by the user, or, if they really trust your app, this context could even be scraped from what's currently on-screen (or which files are currently being worked on).

Another thing I've thought about doing is using a separate keybind (or button/pedal) that appends the transcription directly to a running notes file. I often want to make a note to reference later, but which I don't need immediately. It's a little extra friction to have to actually have my notes file open in a window somewhere.

Will keep an eye on epicenter, appreciate the ethos.