Captions first is not a shortcut

Plenty of videos already carry a text track. Paying to transcribe them again is a habit, not a requirement.

Almost every transcription tool opens the same way. Give us the file, or give us the link, and we will start processing. Processing means audio going somewhere, a queue, and a bill that scales with minutes.

For a large share of the videos people actually want to read, that work has already been done. Platforms publish caption tracks, some human made and some machine made, and those tracks are text you can search, quote and keep. Reaching for a paid pipeline before checking is a reflex worth breaking.

The order that holds up: published captions first, private local speech to text second, and a capped paid provider only when the first two come back empty. That order is cheapest, it is fastest, and it keeps the most audio off other people’s servers. The cost only appears where it is genuinely earned.

The catch is real. Auto generated captions arrive without speaker labels and with unreliable punctuation, so they are better for finding a passage than for publishing one. Some videos have no track at all. That is what the second and third steps are for, and it is why the fallback needs a hard cap rather than a good intention.

Receipt

Source: first party

Cost: Free to read.

Free alternative: Not applicable.

Tested: 2026-07-26

Material connection: Spark builds the Video to Text bench described here, so this argument is about first-party work. Stating it here rather than at the bottom.

The catch: Caption quality varies by platform and by uploader. Treat an auto track as a searchable draft, not as a quotable record.