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Simple self-hosted web application, which can be used to convert audio to subtitles by OpenAI's Whisper model
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| 2026-07-24 | 326 |
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# whisper-website A simple, self-hosted web app for turning audio into text and subtitles, powered by [OpenAI's Whisper](https://github.com/openai/whisper). Upload a file, pick a model, and download `.srt`, `.vtt`, or plain `.txt` - with optional translation.   ## Features - Transcription with any Whisper model size (`tiny` → `large`) - Export as `.srt`, `.vtt`, or plain `.txt` - Optional timestamps - plain text export when they're off - Optional translation of the transcript into another language - No cloud dependency for transcription - everything runs on your own machine ## Quick start (Docker Compose) This is the recommended way to run the app - it also keeps downloaded Whisper models cached between restarts. 1. Install [Docker](https://docs.docker.com/engine/install/) and [Docker Compose](https://docs.docker.com/compose/install/) 2. Clone the repo: ```bash git clone https://github.com/Kabanosk/whisper-website.git cd whisper-website ``` 3. Start the app: ```bash docker compose up -d ``` 4. Open [http://127.0.0.1](http://127.0.0.1) To stop it: `docker compose down`. Your downloaded models stay cached in a Docker volume, so the next `up` won't re-download them. ## Quick start (local, no Docker) 1. Clone the repo and go into it: ```bash git clone https://github.com/Kabanosk/whisper-website.git cd whisper-website ``` 2. Create a virtual environment and install dependencies with [uv](https://docs.astral.sh/uv/): ```bash uv venv uv pip install -r requirements.txt ``` 3. Run it: ```bash cd src uv run run.py ``` 4. Open [http://127.0.0.1:8000](http://127.0.0.1:8000) if it doesn't open automatically You'll also need [ffmpeg](https://ffmpeg.org/download.html) installed and available on your `PATH` for this route - the Docker image already includes it. ## License [MIT](LICENSE)
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Read on GitHubWould you bet a product on this? Bounded 0–100 and slow moving.
matched fp:afde512b18db9ab3, topic:whisper, topic:speech-to-text, readme:speech-to-text