whisper-transcription
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
npx skills add majiayu000/claude-skill-registry --skill whisper-transcription-guia-matthieu-clawfu-skills --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# 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 ```bash 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 ```bash python scripts/main.py transcribe audio.
- When to Use This Skill
- What Claude Does vs What You Decide
- Dependencies
- Commands
- Transcribe Single File
- Batch Transcription
- Transcribe + Translate
- Extract Timestamps
- Examples
- Example 1: Podcast to Blog Post
- Example 2: YouTube Subtitles
- Example 3: Batch Process Interview Library
- Model Selection Guide
- Output Formats
pip install openai-whisper torch ffmpeg-python click Also requires ffmpeg installed on system python scripts/main.py transcribe audio.mp3 --model medium --output transcript.txt python scripts/main.py transcribe video.mp4 --format srt --output subtitles.srt python scripts/main.py batch ./recordings/ --format txt --output ./transcripts/ python scripts/main.py translate foreign-audio.mp3 --to en python scripts/main.py timestamps podcast.mp3 --format json Transcribe 1-hour podcast python scripts/main.py transcribe episode-42.mp3 --model medium Processing time: ~5 min for 1 hour audio on M1 Mac
What does the whisper-transcription skill do?
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
How do I install it?
Run `npx skills add majiayu000/claude-skill-registry --skill whisper-transcription-guia-matthieu-clawfu-skills --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.