The QA Engine Checklist
40 checkpoints run before any dubbed or subtitled episode ships.
Most AI dubbing and subtitling tools give you a single confidence score and call it done. That hides exactly the kind of error that slips past a quick review — a translation that's technically correct but breaks character voice, a lip-sync that's close enough to pass a glance but not a broadcast standard, a terminology choice that contradicts episode 3 while translating episode 9.
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What's Inside
The same checklist Echo9 runs — combining automated checks with native linguist review — before an episode is marked complete.
Translation Accuracy
Meaning, idioms, glossary consistency, and continuity with earlier episodes — not just word-for-word correctness.
Lip-Sync & Timing
Dialogue timing, lip alignment on close-ups, and natural speech rhythm — checked, not eyeballed.
Voice & Emotion Fidelity
Cloned voice matched to character profile, emotional tone preserved, accent and tone reviewed.
Audio Technical QA
Clipping, sync drift, loudness consistency, and AI-generation artifacts caught before delivery.
Cultural & Compliance
Regional sensitivities, age-rating language, subtitle reading speed, and legal requirements.
Series Consistency
Terminology memory, voice bible checks, and sign-off logging across every episode and language.
Use it as-is to audit your current vendor's output, or as a starting point for building your own internal QA standard.
Most teams find gaps in Categories C and F first. The guide also breaks down how to sequence the checklist — which categories can run as an automated first-pass gate, and which need native linguist judgment.
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