Rescript 是一款完全离线、基于转录本运行的浏览器端视频编辑器,用户通过删除自动生成的转录文字即可完成视频剪辑。

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开源协议

MIT

最近更新

2026-07-27

AI 仓库情报摘要
FR-AI / ANALYSIS

为什么值得关注

将本地 AI 转录与单词级编辑和填充词去除结合,全程离线且保护隐私,为实现快速、文本驱动的视频编辑提供了独特工具。

适合谁使用

  • 注重隐私保护工作流程的视频编辑者
  • 希望轻松去除填充词的内容创作者
  • 对浏览器端媒体处理感兴趣的开发者
  • 需要快速基于转录本剪裁的记者或教育工作者

典型使用场景

  • 去除录音中的“嗯”“啊”等填充词
  • 通过删除转录本中不需要的部分从长视频创建短片段
  • 利用说话人标签快速编辑采访素材

项目优势

  • 首次缓存模型后完全离线运行,保障隐私
  • 通过转录本直接进行单词级编辑,简化剪辑过程
  • 一键去除填充词节省时间
  • 使用 ffmpeg.wasm 在浏览器中导出帧精确的 MP4 文件

使用前须知

  • 需要支持 SharedArrayBuffer 的 Chromium 内核浏览器
  • 首次使用需下载约 90 MB 的 AI 模型
  • 仅支持包含音轨的视频,无内置视频特效或转场

README 快速开始

Rescript

Edit videos like you edit text — fully offline, in your browser.

✨ Try it now: rescript.aashuu.tech

Rescript is an open-source, transcript-based video editor. Drop in a video and it is transcribed locally with per-word timestamps and speaker labels. Delete words in the transcript and the corresponding clip is cut from the video. Export the final cut to MP4 — without your video ever leaving your device.

  • 🔒 Private by design — no server, no auth, no uploads; all media processing happens on-device
  • 📝 Word-level editing — select words, press ⌫, the cut follows the text
  • 🧹 Filler removal — one-click cut of "um", "uh", and similar fillers (use Verbatim mode to keep them in the transcript)
  • 🗣️ Speaker diarization — the transcript is grouped by speaker
  • 🎬 Timeline — waveform, word labels, cut regions, playhead, zoom
  • Live preview — playback skips your cuts in real time
  • 📦 In-browser export — frame-accurate MP4 render with ffmpeg.wasm

Stack

PieceTech
AppNext.js + React + TypeScript + Tailwind
Transcriptiontransformers.js running whisper-base_timestamped (WebGPU with WASM fallback) in a Web Worker
Speaker labelspyannote-segmentation-3.0 (ONNX)
Media processingffmpeg.wasm (multi-threaded) for audio extraction and export
Statezustand

Development

npm install     # also copies ffmpeg/onnxruntime WASM into public/vendor
npm run dev     # dev server
npm run build   # production build
npm run lint    # eslint

Open http://localhost:3000 and drop in a video with an audio track.

Note on "offline": the AI models (~90 MB total) are downloaded from the Hugging Face Hub the first time you transcribe, then cached in browser storage. After that, everything — transcription, editing, export — works with the network fully disconnected. Your media and transcript never leave the device; the only third-party request the app makes is anonymous page analytics (Google Analytics), which fails

项目描述

🎬 Open source, transcript-based video editor that lives in the browser.

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