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whishper

plujaAGPL-3.0活跃维护

本地运行的语音转文字工具，带网页界面，用 Whisper 模型把任意音频转成文本，还能翻译和编辑字幕，全程数据不出本机。

Transcribe any audio to text, translate and edit subtitles 100% locally with a web UI. Powered by whisper models!

v3.1.4发布于 2024-09-17 20:19 UTC3,107star +4 / 7 天183fork同步于 2026-11-10 17:43 UTC
语音转文字字幕编辑本地部署Whisper网页界面
对比 GitHub 官网aiaudio-to-textgolangspeech-recognitionspeech-to-text

怎么上手

由 README 提炼，执行前请确认
原文 
docker pull pluja/whishper
硬件要求按 README 说明

支持 NVIDIA GPU 加速，也支持纯 CPU 运行；README 未给出具体显存或型号要求。

纯 CPU 可运行
下载：源码 zip·GitHub Releases（安装包）本站不镜像安装包

项目说明

由 README 自动翻译提炼
没人工点评？写下你的经验

本地跑 Whisper 的音频转写与字幕编辑套件，带完整 Web UI，数据不出本机

本地运行的语音转文字工具，带网页界面，用 Whisper 模型把任意音频转成文本，还能翻译和编辑字幕，全程数据不出本机。

核心能力

  • 用 FasterWhisper 作为后端，CPU 上转写也更快
  • 支持上传文件或从 yt-dlp 支持的 URL 直接转写
  • 导出 TXT、JSON、VTT、SRT 或复制纯文本
  • 内置字幕编辑器，含 CPS 警告与片段拆分插入
  • 通过 Libretranslate 容器把转写结果翻译成多语言

容易踩的坑

主分支已停止更新，作者正在 v4 分支重写；翻译依赖单独的 libretranslate 容器，还需 MongoDB 与 Nginx 一起编排；README 未说明默认端口，需查自托管文档。

内容由模型根据 README 生成，可能不完整或不准确，以官方文档为准。看原文 README

最近发版

5 个版本v3.1.4
全部 release
  1. v3.1.4最新正式版2024-09-17 · 2024-09-17 20:19 UTC
    • Update yt-dlp
  2. v3.1.32024-01-30 · 2024-01-30 18:36 UTC
    查看更新说明

    What's Changed

    New Contributors

    Full Changelog: https://github.com/pluja/whishper/compare/v3.1.2...v3.1.3

  3. v3.1.22024-01-03 · 2024-01-03 13:56 UTC
    查看更新说明

    What's Changed

    • Add CPU_THREADS environment to configure the CPU threads used. It defaults to 4. (#28)

    Full Changelog: https://github.com/pluja/whishper/compare/v3.1.1...v3.1.2

  4. v3.1.12023-12-30 · 2023-12-30 15:40 UTC
    查看更新说明

    What's Changed

    New Contributors

    Full Changelog: https://github.com/pluja/whishper/compare/v3.0.1...v3.1.1

  5. v3.1.0v3.1.0 - large-v3 support2023-11-25 · 2023-11-25 19:06 UTC
    查看更新说明

    Added support for Whisper Large v3 model

    • This release bumps the faster-whisper version to 0.10.0, and adds support for the new OpenAI large-v3 model (#48) .

    More info about the model: https://github.com/openai/whisper/discussions/1762

    Full Changelog: https://github.com/pluja/whishper/compare/v3.0.0...v3.1.0

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    README 原文

    未翻译
    在 GitHub 打开

    whishper banner

    🚧 I am working on a complete rewrite of the project. Progress on this can be seen at v4 branch. Consequently, this branch will not receive any new releases or updates.

    Whishper is an open-source, 100% local audio transcription and subtitling suite with a full-featured web UI.

    Features

    • 🗣️ Transcribe any media to text: audio, video, etc.
      • Transcribe from URLs (any source supported by yt-dlp).
      • Upload a file to transcribe.
    • 📥 Download transcriptions in many formats: TXT, JSON, VTT, SRT or copy the raw text to your clipboard.
    • 🌐 Translate your transcriptions to any language supported by Libretranslate.
    • ✍️ Powerful subtitle editor so you don't need to leave the UI!
      • Transcription highlighting based on media position.
      • CPS (Characters per second) warnings.
      • Segment splitting.
      • Segment insertion.
      • Subtitle language selection.
    • 🏠 100% Local: transcription, translation and subtitle edition happen 100% on your machine (can even work offline!).
    • 🚀 Fast: uses FasterWhisper as the Whisper backend: get much faster transcription times on CPU!
    • 👍 Quick and easy setup: use the quick start script, or run through a few steps!
    • 🔥 GPU support: use your NVIDIA GPU to get even faster transcription times!
    • 🐎 CPU support: no GPU? No problem! Whishper can run on CPU too.

    Roadmap

    • Local folder as media input (#15).
    • Full-text search all transcriptions.
    • User authentication.
    • Audio recording from the browser.
    • Add insanely-fast-whisper as an optional backend (#53).
    • Support for GPU acceleration.
      • Non NVIDIA GPU support. Is it possible with faster-whisper?
    • Can we do something with seamless_communication?

    Project structure

    Whishper is a collection of pieces that work together. The three main pieces are:

    • Transcription-API: This is the API that enables running Faster-Whisper. You can find it in the transcription-api folder.
    • Whishper-Backend: This is the backend that coordinates frontend calls, database, and tasks. You can find it in backend folder.
    • Whishper-Frontend: This is the frontend (web UI) of the application. You can find it in frontend folder.
    • Translation (3rd party): This is the libretranslate container that is used for translating subtitles.
    • MongoDB (3rd party): This is the database that stores all the information about your transcriptions.
    • Nginx (3rd party): This is the proxy that allows running everything from a single domain.

    Contributing

    Contributions are welcome! Feel free to open a PR with your changes, or take a look at the issues to see if there is something you can help with.

    Development setup

    Check out the development documentation here.

    Screenshots

    These screenshots are available on the official website, click any of the following links to see:

    Support

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    Credits

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