Transcribe what was said, translate the meaning instead of the words, generate a new voice, and resync the lips to match it. Picasso IA hosts 488 models, so the whole dubbing pipeline runs from one account instead of four separate tools.
You finished a video in English and someone in Brazil, France or Saudi Arabia cannot follow a word of it. AI video dubbing chains three separate jobs into one pipeline, transcribing what was said, translating the meaning into another language, generating a new voice, and resyncing the speaker's lips, so the video plays as if it were made in that language.
Dubbing has always meant three separate crews: a translator, a voice actor and a studio to record them. AI video dubbing collapses that into one automated pass, and the order of the four steps matters more than any single one of them.
Speech-to-text listens to the original audio and produces a timestamped transcript, word by word, including the pauses. That transcript, not a guess at the video's topic, is what gets translated next, so the output tracks what the speaker actually said rather than a paraphrase written by someone who only watched the video once.
Translation is where most of the quality gap between AI dubbing and a professional dub shows up. A literal, word-for-word translation reads stiffly and, worse, runs a different length than the original: German sentences often run longer than their English source, Mandarin often runs shorter. A translation pass that adapts phrasing to the target language's natural rhythm, rather than forcing a word count match, gives the next two steps a script that is actually speakable.
Text-to-speech then generates the new-language voice track from that translated script, and lip resync moves the speaker's mouth to match the new audio's phonemes and timing. On Picasso IA, the whole chain runs through the Toolkit, where transcription, translation-ready text, voice generation and lipsync models sit next to each other instead of living in four different apps.
A dubbed video makes a real person appear to say things in a language and a voice that is not, strictly, their own. That is a legitimate creative and accessibility tool, and it is also a line worth being deliberate about.
Dubbing your own content, your own footage, your own voice, into another language for your own audience carries no ambiguity: you own the words and the likeness, and localizing them is exactly what the tool is for. The line gets real the moment the video features someone else, especially a public figure, a client, or footage you do not have rights over. Generating a translated version of someone else's video without their knowledge or a rights basis to alter their content is an ethical problem before it is anything else, and in a growing number of places it is a legal one too.
The practical rule is simple: label a dubbed video as AI-dubbed when the audience might otherwise assume it is the person's own voice, and never dub a real person into statements they did not make. Consent is not a footnote to this workflow, it is the workflow's actual boundary.
Not every video dubs equally well, and knowing which category yours falls into before you start saves a round of disappointment. Talking-head explainer content, one person facing the camera, speaking at a measured pace, with the mouth clearly visible, is the best case: the lip resync has a clean, close target to match, and the translated script has room to breathe.
Narration over B-roll is even easier, because there is no mouth on screen to resync at all; the new voice track just needs to land under the visuals at roughly the same pace as the original. Interviews sit close behind, since most of the difficulty is the same single-speaker resync problem, just with more natural, less scripted phrasing to translate.
Fast comedic dialogue is the hard case. Timing is the joke, and jokes rarely survive translation with their rhythm intact; a line that lands in 1.2 seconds in the source language might need 1.6 seconds to make sense in the target one, and now the lips and the punchline are fighting each other. Tight lip-sync close-ups amplify small resync errors that a wider shot would hide entirely, and singing is closer to composition than translation, since a sung line's melody, meter and rhyme rarely map onto another language at all.
Pro tip: dub a thirty-second clip from the hardest part of your video first, usually the fastest dialogue or the tightest close-up, before you commit to processing the whole thing. If that segment holds up, the rest almost always will too.
The table below reflects the same pattern across most footage: the fewer things moving quickly on screen, the more convincingly the dub holds together.
| Content type | How dubbing tends to hold up |
|---|---|
| Narrated explainer (voice over B-roll) | Excellent, no mouth on screen to resync |
| Talking-head interview | Strong, one clear face and a measured pace |
| Fast dialogue scene | Uneven, timing and lip-sync both under pressure |
| Singing | Weak, melody and rhyme rarely survive translation |
Run a short test clip from your own footage through the Toolkit before committing credits to a full video; the pricing page shows what each step costs so there are no surprises partway through a longer project.
Five limits are worth knowing before you publish a dubbed video, because none of them are solved by picking a better model.
If your audience reads faster than they need a new voice, the automatic subtitles workflow skips translation-length problems entirely and keeps the original voice intact.
The full pass runs in five steps, and the only one worth spending real time on is the second.
Yes, mostly. The pipeline transcribes the original speech, translates it, generates a new voice track and resyncs the lips to match it, and for talking-head or narrated content the result is usable straight out of the workflow. What still needs a human pass is the translation quality check, especially on jokes, idioms and anything culturally specific that a script alone will not catch.
It can, if you choose a text-to-speech voice that matches the tone and register you want, though it will not clone the original speaker's exact voice unless you specifically use a voice-cloning model with the rights to do so. Most dubbing work uses a distinct, appropriate voice for the new language rather than attempting to recreate the original one, which is also the more transparent choice when the audience should know they are hearing a dub.
The generation itself typically runs in minutes once the transcript and translation are ready, but budget real time for the translation review and a full watch-through afterward. For a first attempt, expect thirty minutes to an hour end to end, most of it spent checking that the translated script reads naturally rather than waiting on any single generation step.
A word-for-word pass is the wrong target, because languages run different lengths and a literal translation drifts the lips out of sync as the clip goes on. The translation step should adapt phrasing to the target language's natural rhythm while keeping the original meaning, which is also what keeps the timing close enough for the resync step to work cleanly.
Almost always because the translated script ran longer or shorter than the original speech, and that gap compounds sentence by sentence over a longer clip. Short clips rarely show the problem; a two-minute video with a translation that runs even ten percent long can end noticeably out of sync by the final line. Retranslating with length in mind fixes most cases.
Not convincingly, and it is worth knowing that going in rather than after a disappointing result. Singing depends on melody, meter and rhyme lining up with the music, and translation does not preserve any of those, so a sung line dubbed into another language usually reads as spoken words forced onto a tune that was not written for them. Spoken narration and dialogue are the reliable use case; treat singing as outside it.
If the footage and the voice are not yours, yes. Dubbing a real person into a language and voice that is not their own, without their knowledge or a rights basis to alter their content, is an ethical problem and increasingly a legal one, particularly for public figures. Dubbing your own footage for your own audience does not raise this question; the line is about whose voice and likeness are being changed.
Picasso IA's catalog includes speech-to-text, translation and text-to-speech models covering a wide range of major languages, and voice quality and naturalness vary by language and by model. It is worth generating a short test clip in your target language and listening to it before you commit to dubbing a full video.
Yes, that is a separate audio layer and the workflow is built to leave it alone. The dubbing pipeline replaces the speech track, not the full mix, so music and effects on a separate stem, or that you re-add afterward, stay untouched. If your source video has speech and music mixed into a single track, isolate the speech first so the new voice track has something clean to swap into.
New accounts get free credits, enough to run the full pipeline on a short clip and judge the result before spending anything further. After that, each step, transcription, translation, voice generation and resync, draws from the same credit balance shown on the pricing page, and there is no separate dubbing-specific plan.
Your video is already finished, and the first dub costs only a few minutes to test. Open the Toolkit and hear it in a language it was never recorded in.
