  Research in the NLP sphere of the Turkic counterparts of Central Asian
languages, namely Kazakh, Uzbek, Kyrgyz, and Turkmen, comes with the typical
challenges of low-resource languages, like data scarcity and a general lack of
linguistic resources. However, in the recent years research has greatly
advanced via collection of language-specific datasets and development of
downstream task technologies. Aiming to summarize this research up until May
2024, this paper also seeks to identify potential areas of future work. To
achieve this, the paper gives a broad, high-level overview of the linguistic
properties of the languages, the current coverage and performance of already
developed technology, application of transfer learning techniques from
higher-resource languages, and availability of labeled and unlabeled data for
each language. Providing a summary of the current state of affairs, we hope
that further research will be facilitated with the considerations we provide in
the current paper.
