
How to write role context for live translation
Separate audience, category, tone, and exact terminology into a maintainable translation role, then regression-test it against one real recording.
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Separate audience, category, tone, and exact terminology into a maintainable translation role, then regression-test it against one real recording.

Design bilingual live captions around language hierarchy, line length, contrast, placement, and real mobile previews instead of the OBS canvas alone.

Classify viewer impact, isolate the failed layer, choose a safe fallback, and verify recovery from a viewer device without derailing the main broadcast.

Rehearse audio, recognition, translation, playback, captions, OBS, and the real viewer device with observable evidence before every broadcast.

Compare local and cloud recognition by audio movement, network dependency, device load, and audit questions instead of treating privacy as a label.

Record host, translated speech, and programme mix on separate OBS tracks while retaining a complete track for ordinary playback and platform checks.

Trace silent translated playback across synthesis, virtual cable, OBS monitoring, stream tracks, and the platform instead of reinstalling blindly.

Use OBS sidechain compression to lower music during translated playback, with verified starting values, test order, and misrouting checks.

Choose between interrupting, preserving, or clearing a live TTS queue based on content risk, with a repeatable stress test for translated playback.

Tune VAD silence timeout from observable failures such as split model numbers, merged sentences, and late finals, using one repeatable recording.

Run every candidate against one fixed recording, compute word error rate, and read the error mix to locate the real problem. Plus latency and cost basis.

Recognition-layer and translation-layer term lists have different limits. What the official docs say about phrase counts, boost values, and why one layer fails.