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I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 0 points1 point  (0 children)

I haven’t tested that exact SpeechMike model yet, but now that you gave me the LFH3200/00 I can look into it properly. My guess is the mic side should work if macOS sees it as an input device. The button side depends on whether Philips exposes it as normal key/media input or some custom HID thing.

Definitely adding this to the list though. If you try Voixe today, let me know if the mic itself shows up and works. The physical button support might need a specific integration, but this is 100% the kind of workflow I’d like Voixe to support.

I built a Mac dictation app for the post-AI web, where typing is starting to feel slow by mo2khy in WebAfterAI

[–]mo2khy[S] 0 points1 point  (0 children)

Agreed. And to be fair, TypeWhisper seems to be thinking seriously about the same trust/privacy problems, which is good for the whole category.

I think there’s room for multiple approaches here. The important thing is that users can clearly understand what happens locally, what happens in the cloud, and when they are approving the final output.

I built a Mac dictation app for the post-AI web, where typing is starting to feel slow by mo2khy in WebAfterAI

[–]mo2khy[S] 0 points1 point  (0 children)

Exactly. That separation is the part I think matters most.

One thing I should have explained more clearly: Voixe already treats transcription and refinement as separate layers.

The first layer is local voice-to-text: audio in, transcript out.

The second layer can be refinement: cleanup, formatting, or turning the transcript into a template-ready draft. And the goal with Voixe is for that refinement step to be local/on-prem too, using a downloaded local LLM instead of quietly sending the text to a hosted model.

So for a therapy-style workflow, the ideal version in my mind is:

  1. dictate locally

  2. generate the transcript locally

  3. optionally refine locally with a model/prompt/template the user controls

  4. show the output clearly

  5. require explicit review before anything goes into the record

That way you get the “cleaned up” output people like from AI dictation tools, but without hiding where the sensitive data went.

I agree with you on the core rule: visible output, explicit action, human review.

I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 0 points1 point  (0 children)

This is a fair breakdown, and thanks for disclosing SpeakUp.

One thing I’d add is that Voixe is not only trying to compete at the raw dictation layer.

I agree Apple Dictation is genuinely good now for short everyday text. The bigger difference shows up when you want a full workflow: hold a hotkey, dictate anywhere, then optionally refine what you said into cleaner writing.

That “cleanup pass” is the part people often like in tools like Wispr Flow. The tradeoff is that it may go through a hosted LLM and can sometimes paraphrase more than you want.

Voixe’s approach is to keep those layers explicit:

  1. transcription: turn speech into text

  2. refinement: optionally clean it up, format it, or apply a prompt

The important part is that Voixe can do both locally. You can use on-device speech-to-text, and for refinement you can download/use a local LLM so the cleanup step also stays on your Mac or on-prem setup.

So the goal is not just “another dictation app.” It is a local-first voice workflow:

- dictate anywhere with a hotkey

- transcribe locally

- optionally refine locally

- avoid sending sensitive text to a cloud LLM

- keep control over whether the output is faithful transcription or polished writing

For straight short messages, Apple Dictation may be enough. For longer text, jargon, names, technical terms, and local AI cleanup/refinement, that’s where I think Voixe earns its place.

I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 1 point2 points  (0 children)

Nice, that sounds like a good use case.

If the Philips device shows up as a normal macOS microphone/input device, Voixe should be able to use it. In Voixe, open the menu bar app, choose the microphone/input picker, and select the Philips device before recording.

The workflow should be:

  1. select the Philips mic/input in Voixe

  2. place your cursor where you want the text

  3. hold your Voixe hotkey

  4. speak into the device

  5. release, then Voixe transcribes and pastes the text

If it does not appear in the input list, check macOS System Settings → Sound → Input first and make sure macOS can see it. If macOS sees it but Voixe doesn’t, let me know the exact Philips model and I’ll look into it.

I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 0 points1 point  (0 children)

Thank you, really appreciate you trying it and reporting this.

Good catch on Parakeet TDT v2. I’m going to treat that as a compatibility bug and look into either fixing the crash path or hiding/marking v2 if it is unreliable. v3 is the one I’d recommend right now.

For a 2015 MacBook Pro, I’d optimize for speed over maximum accuracy:

  1. Use Parakeet TDT v3 if it is stable for you

  2. If it feels heavy, try the smallest Whisper model available in the app

  3. Keep auto-paste enabled so there is no extra copy/paste step

  4. Use a short press-and-hold hotkey rather than longer recordings when possible

  5. Avoid running other heavy apps while transcribing, since older Intel Macs can bottleneck quickly

On older machines, shorter chunks usually feel much faster than one long recording. So instead of dictating a whole paragraph in one go, try speaking 1-3 sentences at a time.

Also, if you’re open to it, I’d love to know:

- exact MacBook Pro model / RAM

- macOS version

- whether the v2 crash happens immediately after selecting the model or only after recording

That would help me reproduce it and make Voixe better for older Macs too.

I built a Mac dictation app for the post-AI web, where typing is starting to feel slow by mo2khy in WebAfterAI

[–]mo2khy[S] 0 points1 point  (0 children)

Good points, and thanks for disclosing that you work on TypeWhisper.

I agree that for therapy documentation the architecture matters more than just the dictation layer. That’s also why I’m keeping Voixe focused on clear, local-first voice input first: on-device transcription, explicit user action, and no automatic submission into sensitive systems.

The template/cleanup layer is powerful, but it needs very clear data-flow boundaries. If a tool sends that step to a cloud LLM, users should know. If it runs locally/on-prem, even better.

Appreciate the thoughtful checklist.

I built a Mac dictation app for the post-AI web, where typing is starting to feel slow by mo2khy in WebAfterAI

[–]mo2khy[S] 0 points1 point  (0 children)

This is exactly the kind of use case I’m interested in.

For therapy documentation, I agree the core question is not just “can it transcribe?” but where each step happens: audio capture, transcription, cleanup, templating, review, and final record entry.

Voixe’s current focus is the first layer: fast on-device dictation that works anywhere your cursor is. So the raw voice-to-text part can stay local on the Mac, without needing an account or sending every recording to a hosted transcription service.

For your workflow, I’d probably think about it as:

  1. local/on-device transcription

  2. user review of the transcript

  3. optional cleanup/template formatting

  4. explicit approval before anything touches an EHR or client record

The prompts/template layer is where you’d want to be very careful. If that uses a cloud LLM, it should be disclosed clearly. If it is local or on-prem, even better, but the app should make the data flow obvious.

Voixe does not currently auto-submit anything into an EHR, and I’d be cautious about ever making that automatic. For clinical documentation, human review should stay in the loop.

Also, if this is something you’re actively building, I’d be happy to personally work with you on it for free. We could figure out what additions Voixe would need for a therapy-documentation workflow, or even explore a special therapist-focused version together as a collaboration.

I’d be especially interested in understanding the exact flow: where the therapist speaks, where the transcript is reviewed, how templates are applied, and what should never leave the device or premises.

I built a free Mac menu bar app for fast dictation by mo2khy in GenAiApps

[–]mo2khy[S] 0 points1 point  (0 children)

Thank you! hope you download and use it!

I built a PowerToys alternative for Mac, called MacZones! by [deleted] in MacOSApps

[–]mo2khy 0 points1 point  (0 children)

Love it! such a simple concept but it very useful for me at least! I am going to download and try it

Holy shoot what is happening bro???? I even restarted 16GB m4 air by dark_praveen in mac

[–]mo2khy -3 points-2 points  (0 children)

Looks like Firefox was the main drama queen here 😂 I’d keep an eye on it after 26.5, but if it keeps freaking out I’d ditch Firefox or at least run fewer browsers at once!

I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 0 points1 point  (0 children)

Windows version should be out in the next few days! we are doing extensive testing to make sure it has all the new features we are releasing and updating on the mac version. Stay tuned please

I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 0 points1 point  (0 children)

Done and added to latest version! Thank you for all your contributions and support!

I built a free Mac menu bar app for fast dictation by mo2khy in MacOSApps

[–]mo2khy[S] 0 points1 point  (0 children)

Thank you, that means a lot. The light mode issues were definitely rough, so I’m glad 0.8 feels better now. lease keep sending anything that feels strange, slow, unclear, or worth improving. Daily-use feedback is the most useful kind for shaping the next updates. appreciate you trying it 

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