Video conditions matter.
The system has to work with real speakers, camera angles, audio quality, pacing and background conditions rather than only clean laboratory samples.
Multilingual video AI
AI video translation with generated speech and lip synchronisation.
Hatek-Lingua AI is being developed to take a source video, translate the spoken content into another language, generate the translated audio and adjust visible mouth movement so it matches the new speech.
The product is currently in research and development. The programme targets more than 100 languages, including 50 African languages; these figures describe planned coverage rather than current production availability.
YorùbáKiswahiliالعربيةHausa
Source videoTarget-language output
Translation, voice generation and visual speech synchronisation.Yorùbá100+languages planned across the programme
50+African languages planned as a dedicated focus
3main output tasks: translate, generate speech, synchronise video
R&Dcurrent stage of the product
What the product is meant to solve
Localising a video usually requires several separate production steps.
A company that wants one video in several languages may need translation, voice recording, audio editing, video editing and quality review for every language.
Hatek-Lingua AI is being built to bring those stages into one software workflow. A user will provide a video and choose a target language. The system will process the speech, produce translated audio and create a version in which the visible speaker is synchronised to the translated speech.
How it is designed to work
Five stages from source video to translated video.
Each stage solves a different part of the localisation problem. The quality of the final result depends on the stages working together.
01
Speech analysis
Detect what is being said, who is speaking and when each segment occurs.
02
Translation
Translate the meaning of the spoken content into the selected target language.
03
Voice generation
Generate intelligible target-language speech with appropriate pronunciation and timing.
04
Visual speech synchronisation
Adjust the speaker's visible mouth movement so it follows the translated audio.
05
Quality review
Check translation accuracy, pronunciation, timing, visual consistency and known failure cases.
African language focus
The language programme is designed to include languages that are often poorly served by mainstream video localisation tools.
The target is more than 100 languages overall, including 50 African languages.
Supporting a language well requires more than adding its name to a list. The development work includes speech data, translation quality, pronunciation, dialect and accent handling, native-speaker evaluation and testing on real video conditions.
See the language programmeYorùbáWest Africa
HausaWest Africa
IgboWest Africa
KiswahiliEast Africa
AmharicEast Africa
ZuluSouthern Africa
WolofWest Africa
LingalaCentral Africa
isiXhosaSouthern Africa
Who it is for
Organisations that need the same video to work across different languages.
The product is intended for both high-volume professional localisation and smaller teams that cannot manage separate dubbing workflows for every language.
Media
Translate interviews, documentaries, programmes and digital video for additional audiences.
Education
Make lectures, courses and training videos understandable to learners in different languages.
Creators
Publish localised versions of creator videos without rebuilding the production from the beginning.
Enterprise
Localise employee training, product education and internal communication.
Broadcasting
Create additional language versions of news, interviews and regional programming.
Public communication
Translate health, civic, safety and community information for multilingual audiences.
Current development work
The project is focused on the technical work required before public release.
Current work is organised around language data, model development, system integration, evaluation and the preparation of measurable pilot use cases.
Language quality has to be evaluated by people.
Automated metrics are useful, but native-speaker review is important for meaning, pronunciation and naturalness.
Development stages
From model work to a usable product.
The order below describes the intended progression of the project. It does not claim that every stage is already complete.
Language data and model researchCurrent focus
Speech, translation and evaluation workCurrent focus
Integrated translation and voice pipelineNext
Visual speech synchronisation integrationNext
Private testing with defined use casesPlanned
Public product releasePlanned
Contact
Contact Hatek-Lingua AI Research, language, pilot and investment conversations are welcome.
We are interested in working with language experts, researchers, media organisations, educators, infrastructure partners and investors who can contribute to the development or validation of Hatek-Lingua AI.