Transcript-based editing

Clip selection is a reading problem dressed up as an editing problem. You're scanning for the sentences that say something interesting and deciding which ones to keep. Doing that in a timeline means scrubbing back and forth to find the start and end of each candidate; doing it in a transcript means reading paragraphs and deleting unwanted lines.

The 5–10× speed gain compounds over a daily clipping workflow. A team that ships clips every day from yesterday's recordings benefits more than a team that ships clips quarterly.

Transcript editing assumes the transcript is accurate. When the model mishears a proper noun or technical term, the transcript-driven cut is wrong, and you'll usually catch it in playback rather than in the transcript itself. So a transcript-edited clip still wants a 30-second QC pass before publish.

It also doesn't help with creative B-roll work. If you're crafting cutaways and pacing, you're back in a timeline anyway. Transcript editing is for the 80% of clip work that's just "keep these sentences, drop these."

The Clipperz editor opens the transcript and the video side by side. Selecting words in the transcript previews the corresponding clip; deleting them trims the clip. Saved selections become rendered clips. The same transcript powers the export to TXT/SRT and the burned-in captions, so editing once propagates everywhere.