Research

The research areas behind Hatek-Lingua AI.

The project combines language research, speech AI, translation, speech generation, computer vision and audiovisual evaluation. The work is organised around the quality requirements of the final translated video.

Research areas

Five technical areas have to work together.

Improving one component is useful only if the complete system also improves. The research programme therefore evaluates both individual models and end-to-end video output.

01

Speech understanding

Recognition, speaker separation, timing, accents, background noise and mixed-language speech.

02

Spoken-language translation

Meaning preservation, terminology, conversational context and duration-aware translation.

03

Speech generation

Pronunciation, intelligibility, naturalness, pacing and target-language delivery.

04

Visual speech synchronisation

Mouth-motion alignment, temporal stability and preservation of the surrounding face and scene.

05

Language evaluation

Native-speaker review, language-specific test sets, known limitations and repeatable quality criteria.

Data and evaluation loop

Language data has to be connected to measurable evaluation.

A model can appear strong on a small demo while still failing on accents, names, code-switching or real recording conditions. The development process therefore needs data collection, model testing, human review and error analysis to feed into one another.

01Collect and prepare data
02Train or adapt models
03Test on real examples
04Review with language experts
05Analyse failures and improve
Responsible development

Voice and face manipulation require clear safeguards.

The same technology that makes localisation useful can also be misused if consent and provenance are ignored.

The product plan therefore includes consent-aware workflows, appropriate controls around speaker likeness and voice use, clear handling of synthetic output, data protection, and policies for high-risk or deceptive uses. These safeguards need to develop alongside model quality.

Research collaboration

Language experts, universities and technical partners can contribute to the programme.

Useful collaboration includes datasets, native-language evaluation, speech and translation expertise, compute infrastructure and real-world test material.

Contact the research team