Azerbaijani speech recognition for Government
Azerbaijani speech recognition for government. Public bodies require on-premise systems so citizen data never leaves the country.
Secure Azerbaijani Speech Recognition for Public Administration
Allmaz provides on-premise automatic speech recognition (ASR) specifically engineered for the Azerbaijani language. Unlike global speech services that often adapt models from related languages—frequently resulting in fluent but incorrect Turkish text—our solution is built natively for Azerbaijani. This ensures that government bodies can automate the processing of massive volumes of public service records without the risk of unusable outputs or linguistic inaccuracies common in general-purpose commercial and open-source models. Designed for the rigorous requirements of public administration, our solution solves the critical challenge of data sovereignty. By deploying the system on your own internal infrastructure, sensitive citizen data never leaves your building, eliminating third-party data retention and the security risks associated with cloud processing. This architecture allows agencies to achieve full call coverage for QA and compliance while maintaining total control over their digital assets.
Solving Government Operational Challenges
Absolute data sovereignty via on-premise deployment, ensuring citizen audio and transcripts never leave your infrastructure
Predictable budgeting by eliminating per-minute cloud billing, meaning operational costs do not scale with call volume
Enhanced audit transparency and compliance through the ability to search and analyze 100% of the call archive
Superior accuracy on real-world audio, specifically trained to handle background noise, interruptions, and overlapping speech
Significant processing efficiency, performing four to seven times faster than benchmarked cloud speech services
Reduced administrative burden by automating the transcription of interviews, meetings, and public service records
Specialized Models for Public Sector Needs
Chinar-F: High-Volume Production
A compact transducer trained on real Azerbaijani call-centre recordings. Optimized for volume and phone-quality audio, it is the most accurate model for real calls, making 23% fewer word errors than a commercial cloud speech service.
Chinar-L: Document-Grade Accuracy
Engineered for interviews and meetings requiring formal records. It produces punctuation, capitals, and digits, achieving 93–94% word accuracy on clear Azerbaijani speech against human-checked transcripts.
Chinar-P: Minimal Infrastructure
A compact model requiring no GPU that runs 26× faster than real time on four CPU cores. It provides punctuation and capitals with performance on a par with a commercial cloud speech service.
Native Azerbaijani Engineering
Built from the ground up for Azerbaijani rather than adapted from other languages, preventing the common failure where systems return confident but incorrect Turkish text.
Deployment and Implementation
Frequently Asked Questions
How does this solve data sovereignty and security concerns?
The system runs entirely on your own infrastructure. Because no call audio leaves your building and there is no third-party data retention, you maintain total control over sensitive citizen data.
How does the accuracy compare to global cloud speech services?
In head-to-head tests on real call-centre recordings, Chinar-F makes 23% fewer word errors than a benchmarked commercial cloud service. Furthermore, it avoids the common issue of returning Turkish text instead of Azerbaijani.
Can the system handle low-quality audio or noisy environments?
Yes. Unlike models trained on read speech, our models are trained on genuine call-centre recordings, meaning they are designed to handle background noise, interruptions, and overlapping speech.
What hardware is required to run these models?
Depending on your needs, you can use Chinar-P for minimal infrastructure (CPU only), Chinar-F for high-volume production (CPU or GPU), or Chinar-L for high-fidelity documents (GPU).
Is there a way to verify the transcription quality before procurement?
Yes. Visitors can test hosted ASR models for free at chinar.allmaz.az by uploading a recording to receive an editable transcript without requiring an account or credit card.
Secure Your Citizen Data Today
Contact Allmaz to implement on-premise Azerbaijani speech recognition for your government agency.
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