One master video. Ten, twenty or even thirty markets to hit. That "one campaign" you thought of quickly becomes thirty distinct production tasks; translation and subtitling, of course, as well as dubbing and- the thing everybody tends to forget until they hit you-the on-screen text embedded directly within the video itself (captions, callouts, pricing, CTAs, lower thirds, etc.).
This on-screen element typically turns the timeline into a trainwreck. You might be able to easily contract out voice-over or subtitles. However, rebuilding every burned-in graphic on-screen for each language, at the right font-level, with the right animation, synchronized to the nearest frame-well, historically this is a manually re-edited job done once per market.
Let's explore how to condense it from days/weeks down to hours.
Why video localization usually takes so long
In general, a standard workflow for a video ad campaign that hits multiple markets appears as so:
1. Translation-script & on-screen elements, per language (this would be outsourced; can take a few days per lot)
2. Voice-Over/Dubbing-recorded or auto generated, then timed/synced per language
3. Subtitling-timed & formatted per language
4. On-Screen Text Rebuild-every burned-in graphic, subtitle, caption or on-screen text overlay manually duplicated and re-edited in editing software per language (matching original font & animation as closely as possible)
5. QA-quality checking of every output by hand against source material
6. Vendor Management-if multiple vendors have been employed (for translation, voice-over, & editing respectively), a vendor manager is need to facilitate handover and sync all processes.
It's that #4, that hidden cost of on-screen text rebuild that most video localization providers forget to account for, that tends to prolong the overall process as it requires manual video editing, not an automated process, to be done per market. Thus, most "AI Localization" so far has actually only solved only the subtitles & dubbed audio, leaving on-screen text untouched (i.e., in original language).
The Key Detail That Actually Dictates Your Time
Here's the nuance you need to remember: when you consider how to solve the problem of rebuilding burned-in on-screen text, you're building an engine that needs to be executed once, not once per language. An engine that automatically detects the location & animated parameters of an on-screen element and cleanly lifts it off while exposing the original image beneath it, only has to go through this complex "de-layering" process once, irrespective of the number of markets that you intend for this video campaign to serve. Once the de-layered, or clean, base layer exists for this video, adding translated copy with precisely matched fonts and animations is simply a substitution process-meaning you only then need to feed it 30 translated strings of copy, 30 different dubbing scripts, 30 subtitle files etc..
This process doesn't scale linearly per market-it scales roughly flat.
It's exactly what distinguishes solutions that genuinely solve the "burned in graphic" problem from AI solutions, which historically, still leave the on-screen content untouched and require human editors to modify as normal.
The Process in 6 Simple Steps
Here's how an advanced video localization platform gets 30 markets worth of content delivered in under an hour:
1. Upload the video to the platform: You'll only upload a finished flat, export of your video, not project files, and that's the single source of truth.
2. Video is analyzed: The system automatically detects the location & parameters for all on-screen graphics and text, as well as generates a "clean" version underneath each element.
3. Translations are applied per market: All translations, from subtitles & on-screen copy to voice-overs, are drawn from a single, centralized source; this ensures spoken & written elements remain synchronized & not fragmented across multiple vendors & translated twice.
4. Every market renders in parallel: When every translation has been entered & analyzed, each resulting video-translated subtitles, dubbing, and on-screen text-will render and export automatically in parallel.
5. Export final deliverables: Every translated campaign, for all 30 of your target markets, comes back looking identical to the original but with brand-specific foreign language text and audio.
These 5 steps, end to end, take less than 60 minutes with an AI tool like NativeCut, as we work from the top of the video asset and build down, with 30 sets of localization files. It all is a bit quicker when you realize the one big effort required for translating any number of individual on-screen texts from all thirty markets only needs to be performed once.
Where Does this Come In Handy?
This entire approach is ideal for teams distributing premium brand videos, whether that be product launch videos, commercials, trailer campaigns or Hero Hero content, etc. If the goal is not to reinvent and re-create new creative in a target language, but to provide a high-quality, fully localized version of an already completed asset with on-screen text, then this is the crucial piece of your pipeline that would ideally be streamlined first. The brand doesn't want an generic substitution for animated graphics, nor the original language text; they are looking for perfectly-transplanted on-screen branding and text.
Frequently Asked Questions
How long does it typically take to localize a video campaign for multiple countries?
A manually completed workflow can take up to days per language when you factor in individual on-screen graphics rebuilds per each market. If your AI tool can leverage on-screen text extraction, you can deliver an entire campaign with translated subtitles, dubbed audio, and rewritten on-screen text over 30 markets in well under an hour after submission.
Are AI tools able to modify and rewrite on-screen elements or do they simply generate subtitles?
Most AI language tools only handle translated subtitles and voice-overs or dubbing. If they can even do voiceovers. An AI tool for brand marketing or e-learning would look something like the NativeCut "NativeMatch" technology, to remove original text then replace it with an edited and localized portion utilizing original font and animation parameters.
What is the fastest possible way to localize video across 10-30 different markets?
The process of translation and localization will be sped up if you can find an AI that analyzes all the text embedded throughout each video just one time for all 30 of your specified languages. This will save significant video editing and quality assurance work.
Is this type of advanced AI localization suitable for campaigns involving high-end brands, not just simpler videos?
If your campaign involves brand-appropriate typography and animation parameters, then yes; as long as it isn’t a generic templating process. Every tool utilizes automation for the video localization work, though they achieve variable quality for the purpose of serving a campaign or promoting a product. The goal should be brand matching over templating every translated on-screen element across 30 languages.
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NativeCut is a leader of AI-powered video localization and the industry standard for creating fully localized campaign creative. Convert up to 78+ languages for subtitles, voiceover, and burned-in on-screen text from one final video file. Visit nativecut.io to find out more.