Caption review method · October 7, 2026

Correcting AI Captions Without Changing the Speaker's Meaning

A caption correction should help a viewer understand what was said. It should not silently turn a hesitant statement into a confident claim or fill an unclear word with a guess.

My public work includes Caption Studio and Caption Action. This is a proposed human review workflow for generated captions, not a claim that these apps implement every step or that a new accuracy result has been measured.

Listen before rewriting

Keep the original generated caption available while reviewing the corresponding audio. Correct a misheard word when the audio supports the correction. Treat stylistic rewriting as a separate editorial decision: “I think this might work” should not become “This works.”

Review the words that change the claim

Negation: “I did not approve it” and “I did approve it” make opposite claims.
Uncertainty: preserve “might,” “I think,” and other meaningful qualifications.
Names, numbers and units: replay the segment; do not infer a value solely because it fits the topic.
Speaker attribution: do not assign a statement to someone without evidence from the recording.

Keep uncertainty visible

If a word remains unclear after replay, mark it for review instead of replacing it with a confident guess. In an internal review record, retain the timestamp, original text, possible correction and reason for uncertainty. For the viewer-facing caption, choose a consistent convention for genuinely unintelligible speech. An internal placeholder is not automatically ready for publication.

Check the edit in context

Replay the corrected cue with the surrounding sentence. Check that its timing still corresponds to the speech and that splitting the caption has not separated a qualifier from the claim it modifies. Then inspect the actual final video or caption file: an editor preview alone does not establish that the exported captions are present and correct.

A compact correction record

For each meaningful edit, record: cue timestamp; original caption; corrected caption; reason; reviewer judgment; unresolved question. If a translation is also produced, keep the transcript correction and translation review distinct so that a downstream mistake can be traced to the right stage.

Human First AI means preserving the person's voice and keeping the reviewer in control. These review questions also inform ongoing work behind the scenes, without implying that unresolved recognition errors have been solved.