# Recent Advancements and Challenges of Turkic Central Asian Language Processing

arXiv: https://arxiv.org/abs/2407.05006 · HTML: https://mlsanity.com/paper/2407.05006/

## Key facts

- Cited by 6 papers in the map (data through 14 Oct 2026).
- Builds on 38 of its 81 references that are in the map.
- First posted on arXiv 6 Jul 2024.

## Builds on (most cited first, 30 of 38)

- [Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer](https://mlsanity.com/paper/1910.10683/) (2019)
- [Common Voice: A Massively-Multilingual Speech Corpus](https://mlsanity.com/paper/1912.06670/) (2019)
- [The State and Fate of Linguistic Diversity and Inclusion in the NLP World](https://mlsanity.com/paper/2004.09095/) (2020)
- [CCNet: Extracting High Quality Monolingual Datasets from Web Crawl Data](https://mlsanity.com/paper/1911.00359/) (2019)
- [The Belebele Benchmark: a Parallel Reading Comprehension Dataset in 122 Language Variants](https://mlsanity.com/paper/2308.16884/) (2023)
- [Quality at a Glance: An Audit of Web-Crawled Multilingual Datasets](https://mlsanity.com/paper/2103.12028/) (2021)
- [Transfer Learning for Low-Resource Neural Machine Translation](https://mlsanity.com/paper/1604.02201/) (2016)
- [A Monolingual Approach to Contextualized Word Embeddings for Mid-Resource Languages](https://mlsanity.com/paper/2006.06202/) (2020)
- [An Empirical Survey of Data Augmentation for Limited Data Learning in NLP](https://mlsanity.com/paper/2106.07499/) (2021)
- [Modeling Language Variation and Universals: A Survey on Typological Linguistics for Natural Language Processing](https://mlsanity.com/paper/1807.00914/) (2018)
- [Transfer Learning across Low-Resource, Related Languages for Neural Machine Translation](https://mlsanity.com/paper/1708.09803/) (2017)
- [Democratizing Neural Machine Translation with OPUS-MT](https://mlsanity.com/paper/2212.01936/) (2022)
- [From Masked Language Modeling to Translation: Non-English Auxiliary Tasks Improve Zero-shot Spoken Language Understanding](https://mlsanity.com/paper/2105.07316/) (2021)
- [A Large-Scale Study of Machine Translation in the Turkic Languages](https://mlsanity.com/paper/2109.04593/) (2021)
- [Attention-based Fully Gated CNN-BGRU for Russian Handwritten Text](https://mlsanity.com/paper/2008.05373/) (2020)
- [KazNERD: Kazakh Named Entity Recognition Dataset](https://mlsanity.com/paper/2111.13419/) (2021)
- [A Crowdsourced Open-Source Kazakh Speech Corpus and Initial Speech Recognition Baseline](https://mlsanity.com/paper/2009.10334/) (2020)
- [AM2iCo: Evaluating Word Meaning in Context across Low-Resource Languages with Adversarial Examples](https://mlsanity.com/paper/2104.08639/) (2021)
- [Past, Present, Future: A Computational Investigation of the Typology of Tense in 1000 Languages](https://mlsanity.com/paper/1704.08914/) (2017)
- [KazakhTTS: An Open-Source Kazakh Text-to-Speech Synthesis Dataset](https://mlsanity.com/paper/2104.08459/) (2021)
- [HKR For Handwritten Kazakh & Russian Database](https://mlsanity.com/paper/2007.03579/) (2020)
- [A Universal Parent Model for Low-Resource Neural Machine Translation Transfer](https://mlsanity.com/paper/1909.06516/) (2019)
- [KOHTD: Kazakh Offline Handwritten Text Dataset](https://mlsanity.com/paper/2110.04075/) (2021)
- [KazakhTTS2: Extending the Open-Source Kazakh TTS Corpus With More Data, Speakers, and Topics](https://mlsanity.com/paper/2201.05771/) (2022)
- [SimRelUz: Similarity and Relatedness scores as a Semantic Evaluation dataset for Uzbek language](https://mlsanity.com/paper/2205.06072/) (2022)
- [Application of Low-resource Machine Translation Techniques to Russian-Tatar Language Pair](https://mlsanity.com/paper/1910.00368/) (2019)
- [KazQAD: Kazakh Open-Domain Question Answering Dataset](https://mlsanity.com/paper/2404.04487/) (2024)
- [Resources for Turkish Natural Language Processing: A critical survey](https://mlsanity.com/paper/2204.05042/) (2022)
- [UzBERT: pretraining a BERT model for Uzbek](https://mlsanity.com/paper/2108.09814/) (2021)
- [KazSAnDRA: Kazakh Sentiment Analysis Dataset of Reviews and Attitudes](https://mlsanity.com/paper/2403.19335/) (2024)

## Built on by (most cited first, 6 of 6)

- [Overview of the First Workshop on Language Models for Low-Resource Languages (LoResLM 2025)](https://mlsanity.com/paper/2412.16365/) (2024)
- [TurkicNLP: An NLP Toolkit for Turkic Languages](https://mlsanity.com/paper/2602.19174/) (2026)
- [Why Better Cross-Lingual Alignment Fails for Better Cross-Lingual Transfer: Case of Encoders](https://mlsanity.com/paper/2603.18863/) (2026)
- [Multilingual Knowledge Transfer under Data Constraints via Lexical Interventions](https://mlsanity.com/paper/2605.23885/) (2026)
- [KZ-SafetyPrompts: A Kazakh Safety Evaluation Prompt Dataset for Large Language Models](https://mlsanity.com/paper/2605.26947/) (2026)
- [KyrgyzLLM-Bench: Benchmarking Kyrgyz Language Understanding](https://mlsanity.com/paper/2607.17173/) (2026)

## Abstract (arXiv)

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.