Why localize podcasts from transcripts instead of machine-translating raw audio alone?
Text flows into translation memory, glossary control, and reviewer diffs while audio-only MT struggles with laughter, ads, and overlapping guests. Cultural jokes, idioms, and brand voice need adaptation notes—not literal strings pasted into new markets. Searchers type podcast translation workflow, bilingual show notes, dubbing script timestamps, and podcast tmx because terminology drift breaks launches. Legal disclaimers differ by country—never assume English boilerplate translates safely without counsel review. Sponsor blocks need localized disclosure formats before you mux subtitles or ship multilingual RSS feeds. Ai2Done keeps the translate variant operational: lock glossaries, transcribe, import CAT, adapt humor with show approval, then publish captioned or dubbed builds with explicit version stamps.
How to prepare podcast audio for multilingual publishing
- Open Transcribe Podcast, choose the translation-source variant, align source languages, target locales, and banned phrases with localization leads, then read upload caps.
- Export timestamped text with speaker tokens, load brand and legal strings into TM, run MT as assist only, and have humans revise segment by segment.
- Have native reviewers listen to punchlines and dense mouth audio before muxing subtitles, then document caption v2 plus publish dates in each RSS description field.