Highlights from webcam footage

The person brings one raw webcam or talking-head recording full of retakes, false starts and long pauses. You deliver a tight rough cut of the best take of every line, then, once you know what the footage is for, whatever it becomes: the same footage with captions and motion graphics, a news spot, clips, or just the clean cut. The cut is free and local and takes about 10 minutes; record the picks and the person's answers where you keep the job's notes.

Steps

1. Cut the best takes (guide-cut-best-takes, route A: python-find-speech-pauses, then python-cut-best-takes-by-speech-islands): utterances from the sound, each transcribed on its own, the last complete take of each line, cuts inside a sentence checked by their own transcript, pauses squeezed, every edge on the frame grid. Gate: review_approve with the rough cut, its longest remaining pauses in the brief.

2. Ask what the footage is for, and follow the workflow for the answer on the approved cut:

   They want	Follow
   The same video, made exciting: captions, titles and graphics that react to them ("cut my takes and go wild")	workflow-add-captions-and-motion-graphics-to-video, at the intensity they pick
   A news segment: them as the anchor in a studio with a chyron	workflow-green-screen-news-spot from its step 4, the strap copy written as in its step 2
   Short vertical clips of the best moments	guide-select-highlights-from-long-footage on the cut, then workflow-podcast-promo for the clips
   A product walkthrough, and they also recorded their screen	workflow-screen-recording-video (its paper edit replaces this cut)
   Only the clean cut	Loudness (ffmpeg-normalize-loudness) and deliver per the core skill

Choices this workflow makes

• The cut comes first and is approved alone. Tracking, captions and every graphic read the cut's frames; a later re-cut redoes all of them.
• The island cut, not a paper edit, for one file: the takes are in one recording and the person approves the result by watching it.
• Ask, don't assume, what it's for. The same rough cut has become a captioned creator video and a mock news segment.

Dead ends

• Cutting on whisper's word times from the whole file: cut points come from the sound (guide-cut-best-takes); whisper's traps, a "Thank you." on a silent run among them, are whisper-cli-transcribe-with-word-times's.
• Building graphics before the cut was approved: every track, cutout and cue had to be redone after a re-cut.

Worked example

A 70 s webcam read at 1280×720, 30 fps, its sound starting 0.21 s in, with the reporter lines read two or three times. 23 utterances; 5 were "Thank you." on silence. The cut kept the last complete take of three passages, one of them stopped at an energy dip just before a trailing "but" (a cut inside a run of speech, checked by transcribing it). Result: 640 frames in 12 spans, picture and sound both 21.333 s, its transcript word for word the lines picked; free, about 10 minutes. The person wanted a news segment, so it went on to workflow-green-screen-news-spot.