Machine translation for low-resource language pairs is a challenging task. This task could become extremely difficult once a speaker uses code switching. We present the first code-switching Kazakh-Russian parallel corpus.Additionally, 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. This method results in a model beating an existing commercial system by human evaluation.
Maksim Borisov, Zhanibek Kozhirbayev, and Valentin Malykh. 2025. Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop), pages 66–76, Albuquerque, USA. Association for Computational Linguistics.
@inproceedings{borisov-etal-2025-low,
title = "Low-resource Machine Translation for Code-switched {K}azakh-{R}ussian Language Pair",
author = "Borisov, Maksim and
Kozhirbayev, Zhanibek and
Malykh, Valentin",
editor = "Ebrahimi, Abteen and
Haider, Samar and
Liu, Emmy and
Haider, Sammar and
Pacheco, Maria Leonor and
Wein, Shira",
booktitle = "Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)",
month = apr,
year = "2025",
address = "Albuquerque, USA",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2025.naacl-srw.7/",
doi = "10.18653/v1/2025.naacl-srw.7",
pages = "66--76",
ISBN = "979-8-89176-192-6",
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 present the first code-switching Kazakh-Russian parallel corpus.Additionally, 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. This method results in a model beating an existing commercial system by human evaluation."
}
%0 Conference Proceedings
%T Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair
%A Borisov, Maksim
%A Kozhirbayev, Zhanibek
%A Malykh, Valentin
%Y Ebrahimi, Abteen
%Y Haider, Samar
%Y Liu, Emmy
%Y Haider, Sammar
%Y Pacheco, Maria Leonor
%Y Wein, Shira
%S Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop)
%D 2025
%8 April
%I Association for Computational Linguistics
%C Albuquerque, USA
%@ 979-8-89176-192-6
%F borisov-etal-2025-low
%X Machine translation for low-resource language pairs is a challenging task. This task could become extremely difficult once a speaker uses code switching. We present the first code-switching Kazakh-Russian parallel corpus.Additionally, 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. This method results in a model beating an existing commercial system by human evaluation.
%R 10.18653/v1/2025.naacl-srw.7
%U https://aclanthology.org/2025.naacl-srw.7/
%U https://doi.org/10.18653/v1/2025.naacl-srw.7
%P 66-76
[Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair](https://aclanthology.org/2025.naacl-srw.7/) (Borisov et al., NAACL 2025)
Maksim Borisov, Zhanibek Kozhirbayev, and Valentin Malykh. 2025. Low-resource Machine Translation for Code-switched Kazakh-Russian Language Pair. In Proceedings of the 2025 Conference of the Nations of the Americas Chapter of the Association for Computational Linguistics: Human Language Technologies (Volume 4: Student Research Workshop), pages 66–76, Albuquerque, USA. Association for Computational Linguistics.