Open-source transcription that costs $0.02/hour instead of $30/month

What it does

⚠️ Moved to EpicenterHQ/epicenter—see README for redirect - braden-w/whispering

Whispering is now part of Epicenter , an ecosystem of local-first, open-source apps. Everything else remains the same—same tools, same philosophy, samefrom github.com

In the maker’s words, at launch

I built Whispering because I believe transcription is too fundamental a tool to be locked behind paywalls. It's a cross-platform desktop and web transcription app that turns speech into text with a keyboard shortcut, among other things. The app lets you bring your own API key (OpenAI, Groq, etc.) and make direct…

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  Whispering – Open-source, local-first dictation you can trust2025 · github.com · ▲591

  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…

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  Open-source, local-first dictation you can trust

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  I was laid off recently and, instead of looking for another job right away, I decided to build something I always wanted: a transcription tool that respects user privacy. Existing transcription tools often require internet connectivity, send your private audio to cloud servers, or lock you into monthly subscriptions. I wanted something different—so I built WhisperBuddy, a privacy-first AI transcription app that runs entirely on your machine. WhisperBuddy uses OpenAI’s Whisper model (see: https://github.com/openai/whisper). While the model may not always deliver the…

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  Hey HN! I've been working on a side project to create an audio transcription API based on the OpenAI whisper model. Sign up link: https://whisperapi.com I tried to make the API really easy to use and get setup with. Also, because the Whisper model is so good, turns out I can offer the service for about 75% cheaper than what seems like the industry average. I'm always looking to make improvements, so would appreciate any feedback anyone has!

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