An alternative to manual transcription
An alternative to manual transcription: a local, on-prem alternative for Azerbaijani business — see how Chinar compares.
High-Precision Azerbaijani Automatic Speech Recognition
Many businesses currently rely on manual transcription or generic cloud speech services that struggle with the specific nuances of the Azerbaijani language. While global services often claim support, they frequently return fluent Turkish text instead of Azerbaijani—a mistake that can go unnoticed by those unfamiliar with the language—or produce output that is effectively unusable. Allmaz provides a specialized, on-premises automatic speech recognition (ASR) solution built from the ground up for Azerbaijani, rather than being adapted from a related language, ensuring linguistic precision and technical reliability. By deploying this technology on your own infrastructure, you eliminate the risks associated with third-party data retention and the escalating costs of per-minute cloud billing. Our models are specifically trained on genuine call-center recordings, meaning they are optimized for the realities of phone-line quality, including background noise, interruptions, and overlapping speech. This approach allows organizations to move from sampling a few calls to achieving full call coverage, enabling comprehensive QA, deep archive search, and robust evidence for compliance and audit.
Advantages of Localized ASR Deployment
Native Azerbaijani support built specifically for the language, avoiding the common 'Turkish-language' output errors found in global services.
Absolute data sovereignty with on-premises deployment, ensuring no call audio ever leaves your building.
Significant cost reduction by eliminating per-minute cloud billing; operational costs remain stable regardless of call volume.
Superior accuracy on real-world phone audio, with the production model making 23% fewer word errors than commercial cloud alternatives.
Rapid processing speeds, performing four to seven times faster than benchmarked cloud speech services.
Comprehensive operational oversight, enabling 100% call transcription for analytics, QA, and regulatory compliance.
Specialized Models for Every Infrastructure
Chinar-F: High-Volume Production
The default production model and a compact transducer trained on real Azerbaijani call-center recordings. It is the most accurate choice for real calls, scoring 91% word accuracy on clear speech and significantly outperforming commercial cloud services on phone-quality audio.
Chinar-L: Document-Ready Transcripts
A GPU-powered model designed for interviews and meetings where the output becomes a formal document. It automatically handles punctuation, capitalization, and numbers as digits, achieving 93–94% word accuracy on clear Azerbaijani speech, measured against human-checked transcripts.
Chinar-P: Minimal Infrastructure
A compact, CPU-only model that requires no GPU and runs 26× faster than real-time on just four CPU cores. It provides punctuation and capitalization while maintaining performance on a par with a commercial cloud speech service.
Implementing Local Transcription
Frequently Asked Questions
How does this solution differ from global cloud speech services?
Global services often mistake Azerbaijani for Turkish or produce unusable results because they are not built for the language. Our models are trained specifically on Azerbaijani phone audio, providing far higher accuracy and the ability to run locally for better privacy.
Can the system handle low-quality audio or noisy environments?
Yes. Unlike models trained on 'read speech,' our models are trained on genuine call-center recordings, making them resilient to background noise, overlapping speech, and standard phone-line quality.
What hardware is required for deployment?
Depending on your needs, you can use Chinar-L (requires GPU) for maximum document quality, or Chinar-F and Chinar-P, which can run on CPUs. Chinar-P is specifically optimized for minimal infrastructure, running 26× faster than real-time on four CPU cores.
Is there a way to test the accuracy before committing to a deployment?
Yes. Visitors can test hosted ASR models for free at chinar.allmaz.az. You can upload a recording and receive an editable Azerbaijani transcript without needing an account or a credit card.
Are other languages or mixed-language speech supported?
The current models are optimized for Azerbaijani; however, support for Russian and mixed Azerbaijani–Russian speech is currently in development.
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