Recent Advancements and Challenges of Turkic Central Asian Language Processing

Yana Veitsman, Mareike Hartmann


Abstract
Research in NLP for Central Asian Turkic languages - Kazakh, Uzbek, Kyrgyz, and Turkmen - faces typical low-resource language challenges like data scarcity, limited linguistic resources and technology development. However, recent advancements have included the collection of language-specific datasets and the development of models for downstream tasks. Thus, this paper aims to summarize recent progress and identify future research directions. It provides a high-level overview of each language’s linguistic features, the current technology landscape, the application of transfer learning from higher-resource languages, and the availability of labeled and unlabeled data. By outlining the current state, we hope to inspire and facilitate future research.
Anthology ID:
2025.loreslm-1.25
Volume:
Proceedings of the First Workshop on Language Models for Low-Resource Languages
Month:
January
Year:
2025
Address:
Abu Dhabi, United Arab Emirates
Editors:
Hansi Hettiarachchi, Tharindu Ranasinghe, Paul Rayson, Ruslan Mitkov, Mohamed Gaber, Damith Premasiri, Fiona Anting Tan, Lasitha Uyangodage
Venues:
LoResLM | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
309–324
Language:
URL:
https://aclanthology.org/2025.loreslm-1.25/
DOI:
Bibkey:
Cite (ACL):
Yana Veitsman and Mareike Hartmann. 2025. Recent Advancements and Challenges of Turkic Central Asian Language Processing. In Proceedings of the First Workshop on Language Models for Low-Resource Languages, pages 309–324, Abu Dhabi, United Arab Emirates. Association for Computational Linguistics.
Cite (Informal):
Recent Advancements and Challenges of Turkic Central Asian Language Processing (Veitsman & Hartmann, LoResLM 2025)
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PDF:
https://aclanthology.org/2025.loreslm-1.25.pdf