为什么值得关注

它将设备端 Whisper 转录、说话人分离和词语级编辑结合在一起，媒体文件无需上传至任何服务器，为追求隐私的用户提供了云编辑工具的替代方案。

适合谁使用

希望拥有私密工作流的视频编辑与内容创作者
需要快速去除填充词和错误的播客及音频编辑者
需要基于转录快速剪辑的记者和采访人
无法将媒体上传至在线服务的隐私敏感用户

典型使用场景

删除采访转录中的填充词或无关段落来剪辑视频
一键去除播客或语音笔记中的“嗯”、“啊”等填充音
导入已有的 SRT/VTT 转录文件，跳过设备端转录直接编辑
在浏览器中导出逐帧精确的 MP4 或 M4A 最终剪辑版

项目优势

完全隐私保护——无需上传、无需服务器、无需登录，媒体始终留在设备上
词语级精确剪辑，实时预览和时间轴显示剪切区域
支持视频和音频，可选说话人分离功能
开源（MIT 许可），基于现代 Web 技术（WebGPU、SharedArrayBuffer、ffmpeg.wasm）

使用前须知

首次使用需下载 Whisper 模型（约 200-600 MB）和说话人模型，可能花费较长时间
需要基于 Chromium 且支持 SharedArrayBuffer 的浏览器，不兼容所有浏览器
编辑仅限于基于转录的剪切——未生成或导入转录时无法进行裁剪或编辑

README 快速开始

Rescript

Edit video and audio like you edit text — fully offline, in your browser.

✨ Try it now: wassgha.github.io/rescript

Rescript is an open-source, transcript-based media editor. Drop in a video or audio file 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 media. Export the final cut — without your file 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
📥 Import your own transcript — skip Whisper and edit with an SRT, VTT, or JSON caption file
🧹 Filler removal — one-click cut of "um", "uh", and similar fillers
🗣️ 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 (video) or M4A (audio) with ffmpeg.wasm
🎧 Audio files — edit podcasts, voice notes, and interviews the same way as video

Stack

Piece	Tech
App	Next.js + React + TypeScript + Tailwind
Transcription	transformers.js running `whisper-base_timestamped` or `whisper-small_timestamped` (WebGPU with WASM fallback) in a Web Worker
Speaker labels	`pyannote-segmentation-3.0` (ONNX)
Media processing	ffmpeg.wasm (multi-threaded) for audio extraction and export
State	zustand

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 (Whisper Base ~200 MB, or Small ~600 MB, plus a small speaker model) are downloade

项目描述

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

rescript