Augmented Quality Assessment (AQuA)
AQuA seeks to develop capacity and increase the pace of translation quality assurance. AQuA harnesses the latest artificial intelligence (AI) techniques to assist human reviewers in objectively assessing multiple facets of translation quality. AQuA is able to produce an increasingly detailed suite of quality-related diagnostics, with at least five augmented quality assessment methods in the areas of accuracy, clarity, and naturalness.
Testimonials
Additional Description
AQuA helps to develop capacity and increase the pace of Bible translation while ensuring quality throughout the translation community.
To this end, AQuA is creating:
- power tools for translation consultants, which will allow them to do their checking work more thoroughly and more consistently;
- an early warning system for translators, which will alert them to obvious problems so they can address them earlier in the translation process;
- an equalizer for administrators and strategists, which will allow them to compare and evaluate methodologies and products on an equal footing (including new AI-based translation methodologies proposed by TBTA, SIL, and Avodah).
By identifying possibly problematic or anomalous passages in a draft, AQuA accelerates the quality assessment process by helping:
- translators make corrections (and produce an improved draft) prior to consultant checks;
- consultants gain an “at-a-glance” understand of quality across a draft and quickly dig into the relevant, granular quality issues; and
- administrators and project managers track quality across projects to guide strategic allocations of checking resources.
The AQuA team has been working in a multidisciplinary and cross-organizational manner to validate the following methods for efficiently probing the “big three” qualities of Bible translations:
- Accuracy – Semantic similarity, agreement similarity, and word alignment
- Clarity – Automated question answering
- Naturalness – Consistency of readability, reading level
AQuA is currently in private beta. If you are interested in a trial deployment for your project, please email sign up at ai.sil.org/contact