ABSTRACT
01.Method
- Paired, black-box: one source clip × one target language; complete final audio from both systems.
- Timing-sensitive metrics: only the 31 pairs with independently verified source-timeline alignment (40 ms contract; uncertain lanes fail closed).
- Event metrics: the 14 lanes with human-verified laughter or reaction regions.
- Unavailable YouTube lanes: stay explicit, never scored as zero.
- Meaning review: judges the delivered speech; valid paraphrases and tiny background reactions are not errors; CER/WER excluded.
02.The voice: theirs is a stranger's
YouTube's auto-dub speaks in a generic synthetic voice; Familiar re-renders the original speaker's. On the 31 exactly aligned pairs, speaker resemblance to the real speaker:
03.The meaning
Of 528 important source ideas across the 50 reviewed dubs, YouTube changed or lost 145; Familiar 43.
YouTube dubs with an important spoken-meaning issue
Familiar dubs with an important spoken-meaning issue
critical meaning failures, YouTube vs Familiar
04.The scene and the reactions
laughter/reaction shape correlation · 14 event lanes
laughter/reaction loudness error · 14 event lanes
source clips with a usable YouTube auto-dub -- Familiar dubbed all 43
05.Limits
REFERENCES
Dubbing is finally good. See the measurements, then talk with the team about your catalog.
FAMILIAR · THE LAUNCH FILM · 2:31
