An independent research project focused on developing a high-quality automatic speech recognition system for the Armenian language.
Armenian ASR is an ongoing research initiative focused on advancing Armenian speech recognition technology. Operating independently of commercial pressure, the project aims to develop high-fidelity acoustic processing models configured for Armenian speech patterns, dialects, and phonology.
This project is currently in the active research and training preparation stage. We do not claim to have a finished model or state-of-the-art benchmark performances. Our singular objective is to build a high-performance Armenian speech recognition model that is robust, open, and accessible.
A large-scale curated speech collection prepared for automatic speech recognition research.
Tracking our milestones from initial collection to community release.
Gathering diverse spoken Armenian audio sources including audiobooks, media transcripts, and crowd-sourced recordings.
Cleaning, segmenting, transcribing, and quality auditing audio samples to create a structured training corpus.
Setting up transformer-based architectures and self-supervised speech models configured for Armenian phonology.
Testing model accuracy using Word Error Rate (WER) metrics against benchmarks, dialects, and noisy recordings.
Deploying model weights, inference recipes, and open-source validation scripts for research collaboration.
The fundamental objectives guiding our research and engineering decisions.
Developing robust acoustic models that accurately transcribe spoken Armenian, accommodating diverse age groups, accents, and recording conditions.
Applying state-of-the-art deep learning architectures, transformer networks, and self-supervised learning recipes to speech recognition.
Building foundational tools and open-source models that expand the digital presence and technical capabilities of the Armenian language.
Sharing pre-trained models, curated datasets, and research findings openly to foster collaboration among global AI researchers.
Making advanced voice-controlled technology, transcriptions, and digital assistants accessible to all Armenian speakers worldwide.
Using machine learning to document, transcribe, and preserve spoken dialects, oral histories, and linguistic heritage of the Armenian language.
We document our processes and share training scripts openly. Explore our repositories to audit data workflows, track training preparations, or collaborate on code.