How transcript quality is scored
Four dimensions, each on a 0-100 scale. The overall score is the mean. 60 is mediocre, 80 is good, 95 is excellent.
- Formatting: paragraph breaks, capitalization, punctuation. The first thing AI assistants and search engines notice when they read transcripts.
- Clarity: sentence structure, legibility, whether meaning survives the conversion from speech to text.
- Completeness: filler signals, dropped audio,
[inaudible]markers, missing words. The cheapest engines skip the most. - Speaker handling: speaker labels, turn handling, diarization accuracy. The difference between a transcript and a readable conversation.
Why this matters
A transcript is raw material, not the end product. Show notes, blog drafts, captions, search-indexed content, AI summaries, and citation-worthy quotes all inherit the quality of the transcript underneath them. A 60-point transcript becomes a 60-point blog post.
What to do with a low score
If formatting and speaker handling are the weakest dimensions, the underlying tool is usually optimized for raw transcription rather than publication. Re-transcribing the source audio with Wisprs typically lifts formatting and speaker handling by 15 to 25 points, because the engine is tuned for publishable structure rather than word accuracy alone.