AI Dubbing: How to Translate and Lip Sync a Video Ad into Any Language in 2026

Four jobs done in order: adapt the script, generate the voice, sync the delivery, export per market; skipping one is what makes a localized ad feel off in the target market.

Dubbing is not a single button. This guide covers the production side of that job. If you are looking for the definition of lip sync and how the technology works under the hood, start with our guide to AI lip sync instead.

Rewrite the script line by line against the original timecodes, trimming until each line fits its shot, instead of translating the words and compressing the audio afterwards.

A literal translation is the fastest way to kill a good ad. The hook that works in English often relies on an idiom, a rhythm, or a cultural reference that has no equivalent elsewhere, so it has to be rewritten, not converted. Same for the call to action: "link in bio" has a native phrasing in each market, and using the wrong one instantly signals a translated ad.

The constraint nobody anticipates is timing. The same sentence rarely takes the same amount of time to say in two languages, and a script that runs long forces you to speed up the voice, which is immediately audible. Write the translated script against the original timecodes: trim adjectives and subordinate clauses until each line fits its shot, rather than compressing the audio afterwards.

Last, check what you are allowed to say. Price displays, health and finance claims, and guarantee wording are regulated market by market. Get the translated script validated before you spend anything on rendering the video.

Clone when the same speaker has to carry every market and you have their consent; use text-to-speech when you need a native voice per market with no source recording.

Voice quality matters as much as sync quality. In SociaLover, voice generation and dubbing live in Voice & Dubbing (ElevenLabs Multilingual v2 and Eleven v3 voices, OpenAI TTS). Two approaches compete:

Whichever you choose, keep one voice per persona for the entire campaign. A viewer who sees three of your ads in a week will notice a character that changes voice long before they notice an imperfect mouth movement.

With a generated avatar you regenerate the clip per language from the translated script and the target voice, so the mouth is generated for the new audio; with filmed footage you need a third-party service that alters the existing face.

There are two very different production paths here, and they do not have the same cost.

If the speaker is a generated avatar, you do not sync anything: you regenerate the clip per language, feeding the model the translated script and the target voice. The video models handle the delivery and the matching mouth movement in the same pass. Using a reference image as the first frame keeps the same face across all your language versions. Veo 3.1, Kling 3.0, Wan 2.7 and Happy Horse 1.1 all accept one, while the Seedance family refuses a photo of a real person's face, and so did Sora 2, retired on September 24, 2026. In SociaLover, that is Avatar Lab (in your dashboard) for generating the talking avatar, the Editor for assembling and captioning the result, and Creative Resizer for the placements. If you have not built the avatar yet, start with how to choose the avatar for your UGC videos.

If the speaker is real footage you filmed, you need a dedicated dubbing service that alters the existing face. SociaLover does not retouch a filmed performance. Several third-party services and open-source projects cover that use case; check their pricing, their output resolution and above all their terms of use before committing a campaign to them.

Two practical habits make every version easier to sell: favor mid shots over extreme close-ups, since the mouth is the first place a viewer looks for a mismatch, and cut away to the product or to B-roll on the lines where the sync is weakest. Keep the original music and room tone under the new voice. A dubbed ad that loses its audio bed sounds cheaper than one with an imperfect accent.

Languages that share their phonemes and their rhythm: Spanish, Italian and Portuguese dub well into each other, so do German and Dutch, while French to Mandarin is the kind of pair that shows in close-up.

The mouth shapes a viewer reads are vowels and a handful of visible consonants (p, b, m, f, v). Two languages that share them produce a dub that holds in a mid shot without a cutaway: Spanish, Italian and Portuguese between themselves; German and Dutch; the Scandinavian languages between themselves; English and German more than English and Japanese. The harder pairs are the ones where syllable length or rhythm differs sharply, such as a Romance language into Mandarin or Japanese, or a language with long compound words into one with short ones. For those versions, plan more cutaways and shorter on-camera lines from the script stage, not at the export.

Build one master timeline in the Editor, treat each market as an export, caption every version in its own language, and derive the placements with Creative Resizer.

Every language version should ship in the placements you actually buy (9:16 for TikTok, Reels and Stories, 1:1 and 4:5 for the Meta feed, 16:9 for YouTube) which Creative Resizer generates from the same source.

Caption every version in its own language. Feed video plays muted by default on most placements, and in a foreign market captions also rescue the lines where the accent or the sync is imperfect. Adopt a naming convention from the first export (creative / market / language / format / version) otherwise your reporting becomes unreadable the moment you pass twenty files.

Finally, roll out one market before ten. Ship the first localized version, look at how it holds attention against the original, and only then produce the rest of the batch.

A studio dub is quoted per language and per minute, with a voice talent, a session and a re-edit each time; an AI dub is a generation cost per second of video, the same for the first market and the tenth.

The two do not scale the same way. With a studio, every additional language adds a talent fee, a recording session and a re-edit, so the cost of a campaign grows roughly in proportion to the number of markets. With AI, the script adaptation is the only step that still costs human time per market; the voice is generated in Voice & Dubbing, the talking clip is re-rendered in Avatar Lab, and both are billed in tokens per second of audio and video, at the same rate whether it is your first market or your tenth. The second thing that changes is the cost of a mistake: a wrong line in a studio dub is a new session, in an AI dub it is a new render of that shot.

We give no dollar figures here because studio quotes vary too much by market and by talent to be summarized honestly. What you can price exactly is the AI side: the token rates per model and the tokens included in each plan are on the pricing page.

Timing, distant phonemes, irreversibility, consent and market-specific claims: five limits that are decided before the render, not after.