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A Web UI for easy subtitle using whisper model.
| Date | Stars |
|---|---|
| 2026-07-24 | 2839 |
| 2026-07-25 | 2839 |
| 2026-07-28 | 2841 |
| 2026-07-30 | 2843 |
| 2026-08-06 | 2843 |
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# Whisper-WebUI
A Gradio-based browser interface for [Whisper](https://github.com/openai/whisper). You can use it as an Easy Subtitle Generator!
## Notebook
If you wish to try this on Colab, you can do it in [here](https://colab.research.google.com/github/jhj0517/Whisper-WebUI/blob/master/notebook/whisper-webui.ipynb)!
# Feature
- Select the Whisper implementation you want to use between :
- [openai/whisper](https://github.com/openai/whisper)
- [SYSTRAN/faster-whisper](https://github.com/SYSTRAN/faster-whisper) (used by default)
- [Vaibhavs10/insanely-fast-whisper](https://github.com/Vaibhavs10/insanely-fast-whisper)
- Generate subtitles from various sources, including :
- Files
- Youtube
- Microphone
- Currently supported subtitle formats :
- SRT
- WebVTT
- txt ( only text file without timeline )
- Speech to Text Translation
- From other languages to English. ( This is Whisper's end-to-end speech-to-text translation feature )
- Text to Text Translation
- Translate subtitle files using Facebook NLLB models
- Translate subtitle files using DeepL API
- Pre-processing audio input with [Silero VAD](https://github.com/snakers4/silero-vad).
- Pre-processing audio input to separate BGM with [UVR](https://github.com/Anjok07/ultimatevocalremovergui).
- Post-processing with speaker diarization using the [pyannote](https://huggingface.co/pyannote/speaker-diarization-3.1) model.
- To download the pyannote model, you need to have a Huggingface token and manually accept their terms in the pages below.
1. https://huggingface.co/pyannote/speaker-diarization-3.1
2. https://huggingface.co/pyannote/segmentation-3.0
### Pipeline Diagram
# Installation and Running
- ## Running with Pinokio
The app is able to run with [Pinokio](https://github.com/pinokiocomputer/pinokio).
1. Install [Pinokio Software](https://program.pinokio.computer/#/?id=install).
2. Open the software and search for Whisper-WebUI and install it.
3. Start the Whisper-WebUI and connect to the `http://localhost:7860`.
- ## Running with Docker
1. Install and launch [Docker-Desktop](https://www.docker.com/products/docker-desktop/).
2. Git clone the repository
```sh
git clone https://github.com/jhj0517/Whisper-WebUI.git
```
3. Build the image ( Image is about 7GB~ )
```sh
docker compose build
```
4. Run the container
```sh
docker compose up
```
5. Connect to the WebUI with your browser at `http://localhost:7860`
If needed, update the [`docker-compose.yaml`](https://github.com/jhj0517/Whisper-WebUI/blob/master/docker-compose.yaml) to match your environment.
- ## Run Locally
### Prerequisite
To run this WebUI, you need to have `git`, `3.10 <= python <= 3.12`, `FFmpeg`.
**Edit `--extra-index-url` in the [`requirements.txt`](https://github.com/jhj0517/Whisper-WebUI/blob/master/requirements.txt) to match your device.<br>**
By default, the WebUI assumes you're using an Nvidia GPU and **CUDA 12.8.** If you're using Intel or another CUDA version, read the [`requirements.txt`](https://github.com/jhj0517/Whisper-WebUI/blob/master/requirements.txt) and edit `--extra-index-url`.
Please follow the links below to install the necessary software:
- git : [https://git-scm.com/downloads](https://git-scm.com/downloads)
- python : [https://www.python.org/downloads/](https://www.python.org/downloads/) **`3.10 ~ 3.12` is recommended.**
- FFmpeg : [https://ffmpeg.org/download.html](https://ffmpeg.org/download.html)
- CUDA : [https://developer.nvidia.com/cuda-downloads](https://developer.nvidia.com/cuda-downloads)
After installing FFmpeg, **make sure to add the `FFmpeg/bin` folder to your system PATH!**
### Installation Using the Script Files
1. git clone this repository
```shell
git clone https://github.com/jhj0517/Whisper-WebUI.git
```
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Would you bet a product on this? Bounded 0–100 and slow moving.
matched fp:766f667d6c5bb300, topic:whisper, readme:speech-to-text, readme:transcription
matched fp:766f667d6c5bb300, topic:pytorch
matched fp:766f667d6c5bb300, topic:gradio, desc:web ui