Whisper Transcription

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

Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

• Author: guia-matthieu
• Source: guia-matthieu/clawfu-skills
• License: MIT
• Homepage: https://clawfu.com

Install and usage instructions live in the source repository linked above.