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whisper-transcription

@guia-matthieu · 收录于 1 周前

Transcribe audio and video files to text using OpenAI Whisper. Use when: converting podcasts to blog posts; creating video subtitles; extracting quotes from interviews; repurposing video content to text; building searchable audio archives

场景播客转文字视频加字幕采访整理

适合你，如果经常需要把录音或视频内容变成可搜索的文字。

/ 下载安装
whisper-transcription.skill双击,或拖进 Claude 桌面版 / Cowork,即完成安装↓ .skill↓ .zip
用别的 agent?下载 .zip 解压,把文件夹放进它的技能目录
Claude Code~/.claude/skills/(项目级 .claude/skills/)
Codex CLI~/.codex/skills/
Cursor自动读取上面两处目录
其他工具见其文档的「skills」目录;两个下载是同一份文件,只是名字不同
/ 通过 npx 安装 校验哈希
npx oh-my-skill add guia-matthieu/clawfu-skills/whisper-transcription
/ 通过 bash 安装
curl -fsSL https://oh-my-skill.com/install.sh | bash -s -- guia-matthieu/clawfu-skills/whisper-transcription
/ 已经装过?验证本机副本,不用重装
npx oh-my-skill verify guia-matthieu/clawfu-skills/whisper-transcription
安装目标可用 --agent / --scope 或 --to 明确指定;省略时只会在唯一已存在的 agent 目录上自动选择,零命中或多命中会停止并提示。content_hash 缺失或不一致均拒装。
132GitHub stars
~937最小装载
~3.1K含声明引用
~3.1K文本包总量
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怎么用

技能原文 SKILL.md作者撰写 · MIT · a69bf67

Whisper Transcription

Transcribe any audio or video to text using OpenAI's Whisper model - the same technology powering ChatGPT voice features.
When to Use This Skill
  • Podcast repurposing - Convert episodes to blog posts, show notes, social snippets
  • Video subtitles - Generate SRT/VTT files for YouTube, social media
  • Interview extraction - Pull quotes and insights from recorded calls
  • Content audit - Make audio/video libraries searchable
  • Translation - Transcribe and translate foreign language content
What Claude Does vs What You Decide

| Claude Does | You Decide | |-------------|------------| | Structures production workflow | Final creative direction | | Suggests technical approaches | Equipment and tool choices | | Creates templates and checklists | Quality standards | | Identifies best practices | Brand/voice decisions | | Generates script outlines | Final script approval |

Dependencies
pip install openai-whisper torch ffmpeg-python click
# Also requires ffmpeg installed on system
# macOS: brew install ffmpeg
# Ubuntu: sudo apt install ffmpeg
Commands
Transcribe Single File
python scripts/main.py transcribe audio.mp3 --model medium --output transcript.txt
python scripts/main.py transcribe video.mp4 --format srt --output subtitles.srt
Batch Transcription
python scripts/main.py batch ./recordings/ --format txt --output ./transcripts/
Transcribe + Translate
python scripts/main.py translate foreign-audio.mp3 --to en
Extract Timestamps
python scripts/main.py timestamps podcast.mp3 --format json
Examples
Example 1: Podcast to Blog Post
# Transcribe 1-hour podcast
python scripts/main.py transcribe episode-42.mp3 --model medium

# Output: episode-42.txt (full transcript with timestamps)
# Processing time: ~5 min for 1 hour audio on M1 Mac
Example 2: YouTube Subtitles
# Generate SRT for video upload
python scripts/main.py transcribe marketing-video.mp4 --format srt

# Output: marketing-video.srt
# Upload directly to YouTube/Vimeo
Example 3: Batch Process Interview Library
# Transcribe all recordings in folder
python scripts/main.py batch ./customer-interviews/ --model small --format txt

# Output: ./customer-interviews/*.txt (one per audio file)
Model Selection Guide

| Model | Speed | Accuracy | VRAM | Best For | |-------|-------|----------|------|----------| | tiny | Fastest | ~70% | 1GB | Quick drafts, short clips | | base | Fast | ~80% | 1GB | Social media clips | | small | Medium | ~85% | 2GB | Podcasts, interviews | | medium | Slow | ~90% | 5GB | Professional transcripts | | large | Slowest | ~95% | 10GB | Critical accuracy needs |

Recommendation: Start with small for most marketing content. Use medium for client deliverables.

Output Formats

| Format | Extension | Use Case | |--------|-----------|----------| | txt | .txt | Blog posts, analysis | | srt | .srt | Video subtitles (YouTube) | | vtt | .vtt | Web video subtitles | | json | .json | Programmatic access | | tsv | .tsv | Spreadsheet analysis |

Performance Tips
  1. GPU acceleration - 10x faster with CUDA GPU
  2. Audio extraction - Script auto-extracts audio from video
  3. Chunking - Long files auto-split for memory efficiency
  4. Language detection - Automatic, or specify with --language
Skill Boundaries
What This Skill Does Well
  • Structuring audio production workflows
  • Providing technical guidance
  • Creating quality checklists
  • Suggesting creative approaches
What This Skill Cannot Do
  • Replace audio engineering expertise
  • Make subjective creative decisions
  • Access or edit audio files directly
  • Guarantee commercial success
Related Skills
  • [video-processing](../video-processing/) - Extract audio from video
  • [youtube-downloader](../youtube-downloader/) - Download videos to transcribe
  • [content-repurposer](../content-repurposer/) - Transform transcripts to content
  • [podcast-production](../../audio/podcast-production/) - Create podcasts
Skill Metadata
  • Mode: cyborg
category: automation
subcategory: audio-processing
dependencies: [openai-whisper, torch, ffmpeg-python]
difficulty: beginner
time_saved: 10+ hours/week
按 MIT 许可原样转载,未经改动 · 在 GitHub 查看 →

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