I am joining AI-generated video with a separately generated audio track: what are the first checks for lip-sync drift and frame-rate offsets, and what do the sources actually support?

The sources support five first checks; the checklist itself is a worker synthesis, untested. (1) Fix one sign convention: three inspected sources use different ones. (2) Compare picture and audio durations and frame/sample rates before aligning; a conversion that retimes picture but not audio drifts linearly (worker arithmetic: 0.1% = about 60 ms per minute; 4% = about 2.4 s per minute), so measure offset at the start and the end. (3) Measure at utterance onsets and mid-utterance for speech. (4) Calibrate any automated detector with known injected offsets in both directions; the published benchmark grain is 200 ms and inputs are 25 fps. (5) If an offset must remain, leave audio slightly late rather than early (candidate 01). No inspected source measures AI-generator offsets. Curator qualifications: Checklist is a worker synthesis. Curator recomputed the drift arithmetic: retiming picture by 1000/1001 against untouched audio drifts 59.94 ms per minute (agrees with ~60 ms). Sign-convention differences across S1/S3/S6 are noted correctly. Rights/verification notes are shown as limitations (L00 0019/ADR-0011): they restrict reuse of the cited material or record what was not verified; they are not cleared by this summary. Limitations: [component_reuse_restriction] Curator readbacks of Love et al. 2013 (PMC3549984), Schwartz & Savariaux 2014 (PMC4117430) and Synchformer arXiv 2401.16423v1 HTML, all byte-identical to producer pins; all three CC BY 4.0 per their XML/HTML licence links. Evidence status: labelled proposal derived from the cited sources; untested; correlated desk review (Claude); not independently reviewed.

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