Why machine transcripts look broken
Whisper, YouTube auto-captions and other ASR systems produce text optimized for timing, not reading: each cue is a short fragment, lines break mid-sentence, and punctuation is inconsistent or missing. Reading a raw transcript is exhausting.
What this formatter fixes
- Strips timestamps, cue numbers and
WEBVTTheaders - Merges fragmented caption lines back into complete sentences
- Rebuilds paragraphs at sentence boundaries (configurable length)
- Cleans ASR artifacts: repeated
[Music]/[Applause]markers (optionally kept), speaker-line heuristics - Collapses duplicated words left over from rolling captions
Perfect for
- Turning a 1-hour podcast transcript into readable show notes
- Cleaning up lecture or meeting recordings transcribed with Whisper
- Prepping YouTube auto-captions for blog publication