whisper-transcriber

Offline speech-to-text (ASR) using whisper.cpp (whisper-cli) + ffmpeg. Supports batch transcription, timestamps, SRT/TXT/JSON outputs, and model download. Cross-platform: macOS/Linux; Windows via WSL2 (recommended).

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Install skill "whisper-transcriber" with this command: npx skills add vvusu/whisper-transcriber

🎤 Whisper Transcriber（离线语音转文字）

基于 whisper.cpp / whisper-cli 的离线语音识别技能。

快速使用

  • 安装依赖（跨平台自动检测）：
bash <SKILL_DIR>/scripts/install.sh
  • 转写一个音频文件：
bash <SKILL_DIR>/scripts/transcribe.sh voice.ogg
  • 批量转写目录 + 输出 SRT：
bash <SKILL_DIR>/scripts/transcribe.sh ./recordings -b -s

跨平台说明（Windows 推荐 WSL2）

  • macOS / Linux：使用 scripts/install.sh
  • Windows：推荐 WSL2（Ubuntu），在 WSL 内按 Linux 方式运行本 skill（最稳）

WSL 内安装/使用：

bash <SKILL_DIR>/scripts/install.sh
bash <SKILL_DIR>/scripts/transcribe.sh voice.ogg

说明：原生 Windows 环境下 whisper-cli 的安装来源/包名不统一，公开发布时容易造成安装失败；因此本 skill 默认建议 WSL2。

可配置项（环境变量）

无需改脚本，直接用环境变量覆盖默认值：

  • WHISPER_DEFAULT_MODEL（默认 base）
  • WHISPER_DEFAULT_LANG（默认 zh）
  • WHISPER_MODEL_DIR（默认 <SKILL_DIR>/assets/models）
  • WHISPER_MODEL_DIR_USER（默认同 WHISPER_MODEL_DIR，自动下载的默认目录；如你想把模型放到别处再覆盖此变量）
  • WHISPER_TEMP_DIR（默认 ${TMPDIR:-/tmp}；每次运行会在其下 mktemp 创建独立临时目录并自动清理）

目录结构

  • scripts/transcribe.sh：主转写脚本（支持批量、SRT/TXT/JSON）
  • scripts/install.sh：跨平台安装依赖 + 可选下载模型
  • scripts/install.ps1：Windows（非 WSL）best-effort 安装/下载（不作为默认推荐路径）
  • assets/models/：模型默认下载/存放位置（仓库通过 .gitignore 忽略大模型文件，避免提交/发布）
  • config.json：默认配置（发布/维护用，脚本通过环境变量覆盖即可）

需要更细的用法/参数说明：直接运行 bash <SKILL_DIR>/scripts/transcribe.sh --help。

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