whisper.api
A ready API for speech-to-text with per-user access control.
whisper-localは、drajbが公開しているオープンソースの音声プロジェクトです(GitHub: drajb/whisper-local)。GitHubスターは89、フォークは24で、MITライセンスの下で公開されています。GitHubでの最終更新は2026年9月29日です。
Free, open source, 100% offline AI dictation for Windows & macOS.
The README documents setup; start with the install section.
Decide what you want whisper-local to do first — free, open source, 100% offline AI dictation for Windows & macOS. Wisp.
Pull the latest changes to stay current with fixes.
Change the config to match your workflow, then run it daily.
Working accessibility support built in.
Working ai dictation support built in.
Type by speaking anywhere.
Working faster whisper support built in.
Readable code that is easy to modify.
Use it freely, even commercially.
Download the source and move into the project folder.
git clone https://github.com/drajb/whisper-local.git
cd whisper-localInstall the Python dependencies from the project.
pip install -r requirements.txtLaunch with the project entry point — check the README for the exact command.
python main.py # see README for the exact entry pointYes. It is MIT licensed, so you can use it freely, including commercially, with attribution.
No. It is a self-run project — clone it and run it on your own machine. Some features may optionally call external APIs; check the README.
Yes, that is the point. The code is public, so you can run, modify, and host it yourself.
It is released under MIT. Read the LICENSE file in the repo for the exact terms.
Start with the README, then the issue tracker on the GitHub repo at drajb/whisper-local, where maintainers and users answer questions.
A ready API for speech-to-text with per-user access control.
Fast local speech-to-text across 16+ model families, powered by ggml.
Local-first voice AI runtime: transcription, diarization, TTS, cloning.
Free offline Whisper dictation for Windows, macOS, and Linux.
Free, open source, 100% offline AI text-to-speech for macOS, Windows & Linux.
Free and open source offline voice dictation for Windows, Linux, and macOS.
LibreAIカタログに掲載された音声プロジェクトの中で最もスターの多いもの — whisper-localが合わなかった場合に検討したい、現実的な候補リストです。
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Robust Speech Recognition via Large-Scale Weak Supervision
1 min voice data can also be used to train a good TTS model! (few shot voice cloning)
Clone a voice from 5 seconds of audio and generate arbitrary speech in real time
Port of OpenAI's Whisper model in C/C++
カタログの中でwhisper-localとスター数が近い音声プロジェクト — 前後の棚もそのまま見て回れます。
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