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Show HN: Ghost Pepper – Local hold-to-talk speech-to-text for macOS
A privacy-focused, 100% local, open-source speech-to-text application for macOS, designed for coding, emails, and as a voice interface for other agents.
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AI Executive Synthesis
A privacy-focused, 100% local, open-source speech-to-text application for macOS, designed for coding, emails, and as a voice interface for other agents.
Ghost Pepper addresses a significant privacy concern in the speech-to-text market by ensuring '100% local models' and 'no data left my computer.' This positioning is highly attractive to developers and businesses handling sensitive information, where cloud-based transcription services pose data security risks. Its open-source nature further enhances trust and allows for community-driven development and customization. The application's utility for 'coding and emails' and potential as a 'voice interface for my other agents' highlights its versatility in professional workflows. This product taps into the growing demand for privacy-preserving AI tools, particularly in regulated industries or for sensitive internal use cases.
I built this because I wanted to see how far I could get with a voice-to-text app that used 100% local models so no data left my computer. I've been using a ton for coding and emails. Experimenting with using it as a voice interface for my other agents too. 100% open-source MIT license, would love feedback, PRs, and ideas on where to take it.
Related Ecosystem & Alternatives
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Deep-Dive FAQs
What is Ghost Pepper – Local hold-to-talk speech-to-text for macOS?
Ghost Pepper – Local hold-to-talk speech-to-text for macOS is analyzed by our AI as: A privacy-focused, 100% local, open-source speech-to-text application for macOS, designed for coding, emails, and as a voice interface for other agents.. It focuses on Ghost Pepper addresses a significant privacy concern in the speech-to-text market by ensuring '100% local models' and 'no data left my computer.' T...
Where did Ghost Pepper – Local hold-to-talk speech-to-text for macOS originate?
Data for Ghost Pepper – Local hold-to-talk speech-to-text for macOS was aggregated directly from the Hacker News community ecosystem, representing raw developer and early-adopter sentiment.
When was Ghost Pepper – Local hold-to-talk speech-to-text for macOS publicly launched?
The initial public indexing or launch date for Ghost Pepper – Local hold-to-talk speech-to-text for macOS within our tracked developer communities was recorded on April 7, 2026.
How popular is Ghost Pepper – Local hold-to-talk speech-to-text for macOS?
Ghost Pepper – Local hold-to-talk speech-to-text for macOS has achieved measurable traction, logging over 367 traction score and facilitating 171 recorded discussions or engagements.
Which technical categories define Ghost Pepper – Local hold-to-talk speech-to-text for macOS?
Based on metadata extraction, Ghost Pepper – Local hold-to-talk speech-to-text for macOS is categorized under topics such as: Local models, voice-to-text app, macOS, hold-to-talk.
What are some commercial alternatives to Ghost Pepper – Local hold-to-talk speech-to-text for macOS?
Our semantic intelligence engine identifies potential commercial alternatives in the SaaS space, such as Monkey Morse, which offers overlapping value propositions.
How does the creator describe Ghost Pepper – Local hold-to-talk speech-to-text for macOS?
The original author or development team describes the product as follows: "I built this because I wanted to see how far I could get with a voice-to-text app that used 100% local models so no data left my computer. I've been using a ton for coding and emails. Experimenting..."
Community Voice & Feedback
I currently use MacWhisper and it is quite good, but it's great to see an alternative, especially as I've been looking to use more recent models!I hope there will be a way to plug in other models: I currently work mostly with Whisper Large. Parakeet is slightly worse for non-English languages. But there are better recent developments.
https://handy.computer/ already exists?
This is great, and I'm not knocking it, but every time I see these apps it reminds me of my phone.My 2021 Google Pixel 6, when offline, can transcribe speech to text, and also corrects things contextually. it can make a mistake, and as I continue to speak, it will go back and correct something earlier in the sentence. What tech does Google have shoved in there that predates Whisper and Qwen by five years? And why do we now need a 1Gb of transformers to do it on a more powerful platform?
This thread is a support group for people who have each independently built the same macOS speech-to-text app.
Speech-to-text has become integral part of my dev flow especially for dictating detailed prompts to LLMs and coding agents.I have collected the best open-source voice typing tools categorized by platform in this awesome-style GitHub repo. Hope you all find this useful!https://github.com/primaprashant/awesome-voice-typing
I see quite a few of these, the killer feature to me will be one that fine tunes the model based on your own voice.E.G. if your name is `Donold` (pronounced like Donald) there is not a transcription model in existence that will transcribe your name correctly. That means forget inputting your name or email ever, it will never output it correctly.Combine that with any subtleties of speech you have, or industry jargon you frequently use and you will have a much more useful tool.We have a ton of options for "predict the most common word that matches this audio data" but I haven't found any "predict MY most common word" setups.
I see a lot of whisper stuff out there. Are these the same old OpenAI whispers or have they been updated heavily?I've been using parakeet v3 which is fantastic (and tiny). Confused why we're still seeing whisper out there, there's been a lot of development.
That’s awesome! Do you know how it compares to Handy? Handy is open source and local only too. It’s been around a while and what I’ve been using.https://github.com/cjpais/handy
Nice one! For Linux folks, I developed https://github.com/goodroot/hyprwhspr.On Linux, there's access to the latest Cohere Transcribe model and it works very, very well. Requires a GPU though. Larger local models generally shouldn't require a subordinate model for clean up.Have you compared WhisperKit to faster-whisper or similar? You might be able to run turbov3 successfully and negate the need for cleanup.Incidentally, waiting for Apple to blow this all up with native STT any day now. :)
Thank you for sharing, I appreciate the emphasis on local speed and privacy. As a current user of Hex (https://github.com/kitlangton/Hex), which has similar goals, what are your thoughts on how they compare?
Discovery Source
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Deep Research & Science
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