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

• GPU acceleration - 10x faster with CUDA GPU
• Audio extraction - Script auto-extracts audio from video
• Chunking - Long files auto-split for memory efficiency
• 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 - Extract audio from video
• youtube-downloader - Download videos to transcribe
• content-repurposer - Transform transcripts to content
• 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