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Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

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31–40 of 54 posts

Re: Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

#32

Earlier quoted context omitted.

Does the new SpeechAnalyzer API not call Apple Servers? I remember when I was building on the last version, it you wanted real time transcription you needed at least to upload it to Apple Servers for processing.

I think it once did! Now it doesn't - ways to easily verify this: 1) install the dmg in the GH repo 2) turn off wifi 3) use it offline

That doesn’t prove it doesn’t send data if it has the possibility. It could use the offline model only as a fallback.

Re: Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

#33
post #15

Amazing! This is something I wanted to look into too. The Apple Foundation models SDKs are surprisingly cool. I recently started working on a personal productivity app that tries to keep track of all the projects I work on, and the ideas and initiatives within these. It does so by creating a graph of events, fed by Claude transcripts and the git and browser history, then letting FM summarize and describe all events;…

Sounds really interesting, is it open-source by any chance?

Re: Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

#36
post #27

Seems nice! I have been using Handy https://handy.computer/ for a while and I am happy with it (using Parakeet), this seems quite similar in terms of features, except that is uses Apple's APIs.

Big fan of Handy as well. I often mix languages (german/english) and Apple onboard dictation is not working well in these cases. Having the ability to switch models so far has proven to be helpful. I guess Handy should implement the new native Apple APIs though.

Re: Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

#37
post #31

Does the built-in dictation not use these models or why would I use this app instead of Apple's own dictation?

Apple's built in dictation still executes parts of it online and even has a disclosure that it "sends information like your voice input, contacts, and location to Apple."

This project uses the on-device SpeechAnalyzer API directly and makes zero network calls, and since it's open source you can verify that nothing leaves your Mac.

Re: Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

#38
post #28

Strangely, on my macOS 27 Beta build 26A5388g, nothing happens after I finish speaking. No input is transcribed or pasted and nothing is shown in the history. I do see the input being listed to — there's an audio graph animated as I speak (~US English), though it appears to be late in picking up my speech. Only my second "test?" is represented in the graph as it moves leftwards. I went through all the permissions, th…

Sorry about these issues - appreciate all the details. Are you on an Intel Mac by any chance?

Re: Show HN: Yap – OSS on-device voice dictation for macOS with no model to download

#40
post #24

Incidentally, I've been testing a lot of dictation apps and models. I am on macOS Sequoia and intend to skip Tahoe altogether, so newer Apple models were not an option. I also dictate in multiple languages. I mostly use the MacWhisper app until now, but I got frustrated by its slow development and lack of focus and dictation. So I tried the free TypeWhisper app. It works very well, but then I tested multiple models a…

Thank you for testing TypeWhisper and the different models so thoroughly, and for sharing the results. Comparing several engines across multiple languages is already valuable; going one step further and building a faster Whisper Large v3 plugin is a real contribution.

This is exactly why I made TypeWhisper’s engine and plugin layer extensible. The best setup depends heavily on language, hardware, and workload. Your result that Large v3 can run close to Parakeet speeds on a modern Mac is especially interesting, as is your fully local Whisper plus Gemma correction workflow.

If you’re comfortable sharing the plugin or benchmark setup, I’d be very interested in taking a closer look and seeing whether it could benefit more users. Either way, thank you for putting so much time into this and contributing your findings back to the project.

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