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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

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Atualizado há 7 meses

Ver no GitHub ↗ Licença: MIT

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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
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