Remove burned-in subtitles before translating, dubbing, and localizing videos. Built for short dramas, tutorials, and talking-head content.
Clean-master video translation means preparing a subtitle-free, text-cleaned source before localization. The old burned-in text is removed first, so translated subtitles, dubbed voice, and final exports do not compete with source-language captions.
Burned-in subtitles cannot be switched off because they are part of the pixels. Removing them before dubbing keeps the lower frame usable for new subtitles, lip-sync review, and platform-specific layouts.
A regular video translator starts with audio or a transcript. UnmarkAI starts with the visual problem: old subtitles, fixed captions, review labels, and text overlays that block localization.
Use UnmarkAI when the goal is a reusable video localization workflow for teams, not a one-off subtitle file.
Avoid old and new subtitles colliding on screen by creating a subtitle-free master before localization.
Use scene context and glossary rules so product names, character names, and calls to action stay stable.
Plan multi-speaker dubbing around roles, pacing, and emotional tone instead of one flat narration track.
Check subtitles, voice timing, clean-frame quality, and export readiness before publishing.
The workflow is built for authorized videos that need subtitles removed, translated, voiced, and reviewed before publishing.
Start video translationRemove burned-in subtitles, source captions, lower thirds, and temporary review text from authorized footage.
Keep names, product terms, repeated phrases, and episode context consistent before subtitles or voice are generated.
Generate voiceover, align timing, check subtitle safe zones, and prepare reviewed exports for each market.
From talking-head narrations to short drama localization — clean your source, translate with context, and deliver market-ready exports.
| Workflow need | Subtitle-only tools | Dubbing-only tools | UnmarkAI video translation |
|---|---|---|---|
| Remove burned-in subtitles before translation | ✗ No | ✗ No | ✓ Clean master first |
| Handle multi-speaker localization planning | ~ Limited | ~ Often yes | ✓ Speaker-aware workflow |
| Review subtitles, voice, and visual cleanup together | ✗ Manual | ~ Partial | ✓ Unified QA path |
| Prepare batch-ready exports for different markets | ✗ Manual exports | ~ Needs editing | ✓ Localization delivery |
Clean-master video translation means preparing a subtitle-free, text-cleaned version of a video before translating it. UnmarkAI focuses on videos you own or are authorized to edit, so burned-in subtitles, captions, lower thirds, or review text can be removed before new subtitles, voiceover, and localized exports are created.
Burned-in subtitles are part of the video pixels, so they stay visible after translation and can overlap with new captions. Removing them first gives teams a clean frame for target-language subtitles, dubbing, lip-sync review, and different social layouts without cropping away the lower part of the video.
Upload your talking-head or narration video, remove any burned-in source subtitles or on-screen text, then select target languages. The workflow preserves speaker identity and pacing while generating translated voiceover and subtitles for each market.
Yes. Short drama localization is a core use case. Clean episode masters by removing hardcoded source subtitles, then create character-aware dubbed versions with translated captions for each target market. Batch QA ensures consistency across episodes.
Start by creating a clean master — remove all source-language text and subtitles. Then translate and re-export for each target platform and language. This keeps one clean source while generating market-specific versions with localized subtitles, dubbing, and layouts.
The workflow is designed around multi-speaker localization planning. Teams can treat each speaker as a separate voice and review translation, pacing, and role consistency before creating final exports.
Upload an authorized source video, choose target languages, and start the clean-master localization workflow in the UnmarkAI dashboard.
