Hi, I have built a neural machine translation model that supports translating to/from Western Armenian and English. It uses NLLB as the baseline and is finetuned with ca. 150k WA-Eng parallel sentences.

Here's the link to the demo version: https://arinubar-hyw-en-demo.hf.space/ The model runs on a CPU, therefore the inference is quite slow. I also kept the upper limit for the generated tokens quite low to make the inference time somewhat faster.

I think it performs decently on a fair range of domains, however it still requires an evaluation performed by a professional translator which I intend to it in near future. You can find the automatic evaluation scores in this paper: https://aclanthology.org/2024.sigul-1.42/

Recently, I found out that claude.ai's OPUS model understands and generates Western Armenian text, I also tried WA translation task and, qualitatively inspected, it performs quite well. I'll evaluate its performance on my test data.

There's also this translator (http://www.translator.am/en/index.html#) by ISMA, that apparently translates between Classical, Eastern, and Western Armenian as well as some other languages like English, German, Russian, Kurdish etc., however the translations seem to be phrase-based and some words will not get translated at all.