Word-level transcription
Word-level transcription is speech-to-text output in which every individual word carries its own start and end timestamp, rather than timings being given only for whole lines or blocks of text.
A standard transcript tells you roughly when a passage was spoken. A word-level transcript tells you exactly when each word began and ended, usually to within a few tens of milliseconds. That precision is what makes several familiar features possible at all.
What it enables
- →Cuts that land on sentence boundaries rather than on the clock.
- →Captions that highlight word by word as they are spoken.
- →Removing filler words individually without leaving gaps.
- →Searching a video and jumping to the exact moment a phrase occurs.
- →Measuring pace, since words per minute becomes directly countable.
Why block-level timing is not enough
With timings only at the line or paragraph level, the best any editor or tool can do is estimate where inside that span a given word fell. For subtitles displayed as static blocks that is fine. For anything that has to align to speech — a cut, a highlight, a removal — the estimate is wrong often enough to be visible.
The cost of the precision
Word-level output is produced by the same transcription pass, so it rarely costs more than block-level. Modern speech models emit it by default. The real cost is in handling it: a two-hour episode produces tens of thousands of timed tokens, and anything working with them has to be built for that volume.
Clipd transcribes at word level, then cuts on sentences.
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