AI Dubbing and Translation for Video
Build a dubbing pipeline: transcript, translation, voice, timing, mix and native review
A taste of a lesson
My English to German dub sounds like the speaker is in a rush. The translation is accurate. What is wrong?
Accurate is the problem: a faithful German translation is often noticeably longer than the English, so the system speeds up the voice to fit each segment. Fix it upstream. Ask the translator, or prompt the translation step, to condense each line to a target duration or syllable count while keeping meaning. Set a maximum speed up so the voice never exceeds a natural pace. Then have a native German speaker listen for both rush and lost meaning. Can you find one segment where the German is much longer than the English?
Written by the teacher as an example. In your lesson the tutor answers your own questions, and like any AI it can be wrong.
What you will be able to do
- Choose between subtitles, voice over and dubbing for a project
- Design a dubbing pipeline with clear quality gates
- Adapt translations for spoken timing and culture
- Organise native speaker review and handle voice consent
Lesson plan
- 1 Subtitles, voice over or dubbing Choose the localisation format that fits content, audience and budget. Start
- 2 Source transcript and translation Produce an accurate source and a translation written for speech. Start
- 3 Timing adaptation Fit translated lines into the original segment durations. Start
- 4 Voices and consent Select or clone voices responsibly. Start
- 5 Mixing and lip sync Combine dubbed voice with music and effects cleanly. Start
- 6 Native review and release Run quality checks and publish transparently. Start
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About this tutor
An advanced tutor for creators, educators and companies localising video into other languages with AI. You will design a full dubbing pipeline: accurate source transcript, translation adapted for speech and timing, voice choice or consented voice cloning, synthesis, timing alignment, optional lip sync, mixing over a music and effects track, and review by native speakers. We cover language expansion, cultural adaptation, quality checks, cost and when subtitles serve better than dubbing. Consent and disclosure for voices are treated as requirements.
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About the teacher
Voice and audio AI for creators: speech, podcasts, clean up, subtitles, music and consent
9 tutors 387 lessons taught Sample
I teach audio for people who make things: podcasts, videos, courses and apps that talk. I come from sound engineering and radio, so I start with the ear. A tool is only useful if the result sounds right, so we listen, compare and fix. I cover synthetic speech, transcription, dubbing, music and sound effects, and I spend real time on...
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