KyrgyzNLP: Challenges, Progress, and Future

Result code in IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F26%3A8LY7WV44" target="_blank" >RIV/00216208:11320/26:8LY7WV44 - isvavai.cz</a>

Result on the web

<a href="http://dx.doi.org/10.1007/978-3-031-88036-0_1" target="_blank" >http://dx.doi.org/10.1007/978-3-031-88036-0_1</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-031-88036-0_1" target="_blank" >10.1007/978-3-031-88036-0_1</a>

Result language

angličtina

Original language name

KyrgyzNLP: Challenges, Progress, and Future

Original language description

Large language models (LLMs) have excelled in numerous benchmarks, advancing AI applications in both linguistic and non-linguistic tasks. However, this has primarily benefited well-resourced languages, leaving less-resourced ones (LRLs) at a disadvantage. In this paper, we highlight the current state of the NLP field in the specific LRL: кыргыз тили. Human evaluation, including annotated datasets created by native speakers, remains an irreplaceable component of reliable NLP performance, especially for LRLs where automatic evaluations can fall short. In recent assessments of the resources for Turkic languages, Kyrgyz is labeled with the status “Scraping By”, a severely under-resourced language spoken by millions. This is concerning given the growing importance of the language, not only in Kyrgyzstan but also among diaspora communities where it holds no official status. We review prior efforts in the field, noting that many of the publicly available resources have only recently been developed, with few exceptions beyond dictionaries (the processed data used for the analysis is presented at https://kyrgyznlp.github.io/). While recent papers have made some headway, much more remains to be done. Despite interest and support from both business and government sectors in the Kyrgyz Republic, the situation for Kyrgyz language resources remains challenging. We stress the importance of community-driven efforts to build these resources, ensuring the future advancement sustainability. We then share our view of the most pressing challenges in Kyrgyz NLP. Finally, we propose a roadmap for future development in terms of research topics and language resources. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

Czech name

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Czech description

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Type

D - Article in proceedings

CEP classification

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OECD FORD branch

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Project

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Continuities

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Publication year

2025

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection

Lect. Notes Comput. Sci.

ISBN

978-3-031-88035-3

ISSN

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e-ISSN

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Number of pages

37

Pages from-to

3-39

Publisher name

Springer Science and Business Media Deutschland GmbH

Place of publication

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Event location

Bishkek

Event date

Jan 1, 2026

Type of event by nationality

WRD - Celosvětová akce

UT code for WoS article

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