Research
Arabic breaks silently. This is the measurement.
Independent, reproducible evaluation of the Arabic language technology that production work depends on — published from Abu Dhabi. Every finding ships with an open test set, the scorer that produced it, the raw per-item results, and a plain statement of what the measurement does not establish.
One of these reads ٢٠٢٦ as a year. The other reads it as noise.
Arabic is written with two numeral systems and both appear constantly in real copy. The same sentence written with Arabic-Indic digits rather than Western drops from 73% to 7% intelligible on one leading speech engine. A second engine handles both digit forms at 87%, so this is a missing normalisation step rather than a hard problem. It goes unnoticed because voice demos are prose, and prose has no numbers.
The Arabic fix everyone recommends is now the thing breaking your Arabic
arabic_reshaper + python-bidi is the advice in nearly every
tutorial. On any renderer that already does complex-text layout it produces
مكب ابحرم where مرحبا بكم belongs, because
the work happens twice. 15/15 correct without it, 0/15 with it. Filed
upstream against a package downloaded 5.4 million times a month.
Your Arabic PDF is fine. What reads it is not.
A PDF looks right, so it is trusted — but almost nothing that consumes one looks at it. Portals parse it, ATS systems read it, compliance tools scan it. Across four generation routes and three extractors, reversed, ligature-mangled and space-collapsed are three distinct failure modes, not one.
Method
Findings come out of production, not a lab: each began with Arabic breaking in delivered work. Test sets are small and public, scorers are published alongside the results, and every claim is reproducible from the repository.
In two of the three studies the measurement contradicted the assumption it started from, and the write-ups say so. In one, a pass/fail scorer reported a broken configuration as working; adding a middle band is what surfaced the real result. Designing a test that can prove you wrong is most of the work.
Corrections
When four faults were found in the scoring code behind the speech study, a documented correction was published with old-to-new figures per cell rather than a silent revision. A measurement that quietly changes its numbers is worth less than one that never published them.
Elsewhere
Datasets: huggingface.co/syamjithnk · Code: github.com/genviz-ai · Work & evidence
Press and partnership enquiries: get in touch.