Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair
Computation and Language
2025-03-27 v1 Machine Learning
Abstract
Machine translation for low resource language pairs is a challenging task. This task could become extremely difficult once a speaker uses code switching. We propose a method to build a machine translation model for code-switched Kazakh-Russian language pair with no labeled data. Our method is basing on generation of synthetic data. Additionally, we present the first codeswitching Kazakh-Russian parallel corpus and the evaluation results, which include a model achieving 16.48 BLEU almost reaching an existing commercial system and beating it by human evaluation.
Keywords
Cite
@article{arxiv.2503.20007,
title = {Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair},
author = {Maksim Borisov and Zhanibek Kozhirbayev and Valentin Malykh},
journal= {arXiv preprint arXiv:2503.20007},
year = {2025}
}