Captions that drop words change meaning, especially in teaching, where a missing “not” reverses a fact. This free closed-caption accuracy checker compares caption text against the transcript word by word, reporting the match percentage, the words missing from captions, and the words added. No sign-up.
What this tool does
Caption quality is usually judged by feeling: the captions “seemed fine”. Feeling misses dropped words, because readers fill gaps from context without noticing. A word comparison makes the gaps visible and countable.
The match percentage is the headline: transcript words found in captions, divided by all transcript words. Missing words are the fix list, and extra words reveal paraphrasing or mistranscription that may also distort meaning.
This check matters most for teaching videos, where captions are often the only access route for deaf students and a study aid for everyone else. Inaccurate captions in a lesson are not a minor flaw; they are wrong content delivered as if it were right.
How to use it
- Paste the caption text.
- Paste the transcript text.
- Click check captions.
- Fix every missing word that changes meaning, starting with negations and numbers.
Comparison ignores case and punctuation, so “Fractions.” and “fractions” count as the same word. Word order is not checked here; that needs a full alignment review.
Worked example
Captions reading “Welcome to fractions today we learn parts” against a transcript adding “of a whole” give a 77.8 percent match, with “of” and “whole” listed as missing. The teacher adds the missing phrase, and the caption now carries the full definition.
A caption that drops “not” from “do not divide by zero” scores high overall but fails catastrophically on meaning. The missing-word list catches “not” immediately, which is why the list matters more than the percentage.
Extra words reveal a different problem: captions that paraphrase instead of transcribing. A caption adding “basically” everywhere is not wrong in meaning, but it signals an auto-captioning process worth reviewing for accuracy.
Honest limits
Word matching is a proxy, not a proof. It cannot judge timing, speaker labels, sound descriptions, or reading speed, all of which matter for real caption quality. Use this check as a first pass, then review timing by watching the captioned video.
Tips
Fix negations, numbers, and names first. A missing “not”, a wrong digit, or a misspelled name misleads students far more than a dropped filler word, even though all count equally in the percentage.
Common mistakes
The classic mistake is accepting auto-captions above 95 percent without reading the missing list. The remaining 5 percent often contains exactly the words that matter, because auto-captioning fails hardest on technical terms and names.
How it fits your week
Check captions when videos are published, before students rely on them. A five-minute check per video prevents a term of students studying from wrong captions.
Captions are content, and content deserves the same accuracy checks as handouts and slides. A word-by-word comparison is a small discipline with a large payoff: missing words found, meaning preserved, and deaf students receiving the lesson as taught rather than as guessed by software. Paste both texts, read the missing list, fix what changes meaning, and publish captions you would trust for your own learning. Accuracy here is not polish; it is access, and access done halfway is not access at all.
FAQ
What match percentage is good enough?
Aim for 99 percent or higher on teaching content, with zero missing negations, numbers, or key terms. For casual content, 95 percent may suffice, but teaching deserves the higher bar.
Does this check caption timing?
No. Timing, line breaks, and reading speed need a video review. This tool checks words only, which is the foundation timing builds on.
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