audio-transcription-cleanup
Transform messy voice transcription text into well-formatted, human-readable documents while preserving original meaning
When & Why to Use This Skill
The Audio Transcription Cleanup skill is a specialized AI tool designed to transform raw, fragmented voice-to-text outputs into polished, professional documents. It intelligently removes verbal fillers (such as 'um', 'uh', and 'you know'), corrects grammatical inconsistencies, and applies logical formatting like paragraph breaks and headings. Unlike summarization tools, it preserves 100% of the original meaning and detail, making it ideal for creating high-quality records from spoken content in multiple languages including English and Chinese.
Use Cases
- Meeting Minutes Refinement: Convert messy, real-time meeting transcripts into structured, readable documents by removing stutters and adding semantic section headings.
- Podcast & Interview Post-Processing: Clean up raw interview recordings for publication or archival by fixing spoken grammar and organizing dialogue into coherent paragraphs.
- Voice Memo Professionalization: Transform spontaneous voice-recorded ideas or dictations into formal reports or blog drafts while maintaining the author's original intent and natural expression.
- Multilingual Transcript Polishing: Automatically detect and clean up transcripts containing mixed-language content (e.g., English and Mandarin) to ensure linguistic consistency and clarity.
| name | audio-transcription-cleanup |
|---|---|
| description | Transform messy voice transcription text into well-formatted, human-readable documents while preserving original meaning |
Audio Transcription Cleanup
Clean up raw audio transcriptions by removing filler words, fixing errors, and adding proper structure.
Usage
Use the audio_transcript_cleanup.py script to process transcript files:
# Use default output location (~/tmp/cleaned_transcript.md - allows overwrite)
python scripts/audio_transcript_cleanup.py --transcript-file /path/to/transcript.txt
# Specify custom output location (cannot overwrite existing files)
python scripts/audio_transcript_cleanup.py --transcript-file /path/to/transcript.txt --output /path/to/output.md
What It Does
The script automatically:
- Removes verbal artifacts (um, uh, like, you know, 呃, 啊, 那个, etc.)
- Fixes spelling and grammar errors
- Adds semantic paragraph breaks and section headings
- Converts spoken fragments into complete sentences
- Preserves all original information (no summarization)
- Auto-detects language and maintains natural expression
Options
--transcript-file(required) - Path to the transcript file to clean up--output(optional) - Custom output path (default:~/tmp/cleaned_transcript.md)
Output Behavior
- Default location:
~/tmp/cleaned_transcript.md- Allows overwrite - Custom location: Cannot overwrite existing files (raises error if file exists)
Language Support
Auto-detects and works with:
- English
- Chinese (Mandarin, Cantonese)
- Mixed language content
- Multi-speaker transcriptions
Requirements
- Python 3.11+
- Claude CLI must be installed and accessible
- Transcript file must exist at specified path