
Zirek
Fiscal Host: Open Source Collective
Local screen-reader support and neural text-to-speech for languages big vendors ignore, starting with Kurdish (Kurmanji).
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Zirek is live on Open Collective
Zirek has officially joined the Open Source Collective as our fiscal host.If you are new here: Zirek builds local, offline neural text-to-speech and screen-reader support for languages commercial vendors overlook—starting with Kurmanji Kurd...
Published on September 18, 2026 by austek
About
Big vendors don't localize for under-served languages. The commercial market for any single one rarely justifies the investment, leaving speakers of hundreds of languages without screen reader support or local text-to-speech—regardless of community size. Zirek exists to close that gap through open-source infrastructure rather than commercial business cases.
Kurmanji Kurdish—spoken by 15–20 million people with no production-quality screen reader support today—is where this starts, not where it ends. The architecture is deliberately built to generalize:
- dengjen-tashkeel (Arabic diacritic restoration) and dengjen-piper-rs (Piper TTS in Rust) are modular, general-purpose components.
- dengjen-werger, built to organize and retain volunteer translators, is designed around a generic TranslationSource interface so it can target other under-served languages without a rewrite.
- dengjen-nvda and dengjen-tts deliver a fully local, offline NVDA add-on and a Rust inference engine for neural TTS, continuing the sonata-nvda project after its original maintainer stepped back.
A first-generation Kurmanji voice model already exists, trained with two Zarok TV voice actors, proving the pipeline works end-to-end: from raw studio audio to a functional NVDA voice.
Kurmanji's NVDA interface translation has remained open and incomplete since 2018—not due to tooling limitations, but because one-off volunteer enthusiasm rarely translates into sustained maintenance. dengjen-werger targets that exact bottleneck, starting with Kurmanji before expanding outward.
How Funds Are Used
Built today by a solo maintainer on evenings and weekends alongside a full-time engineering role, Zirek is entirely self-funded. While an NLnet Foundation grant application is in progress to fund specific Kurmanji development milestones, this Collective supports the broader infrastructure that grants cannot cover:
- Compute & Training: GPU runtime and cloud compute for training and refining neural voice models.
- Dataset Quality: Compensating voice actors and securing clean, usable audio datasets.
- Testing Rigs & Hardware: Dedicated testing environments to validate add-on builds against real NVDA releases and hardware.
- Contributor Bounties: Moving from pure volunteer goodwill to small stipends for targeted translations and reviews.
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