Abstract
Kazakh language is related to languages with complex morphology and syntax. Today, most machine translation systems consider Kazakh language too, like Google, Yandex, Prompt, etc. This article describes the errors, shortcomings, and problems of machine translation (MT) into the Kazakh language. To analyze errors in machine translation into the Kazakh language, the most popular electronic translation programs were selected. When translating from Russian and English into Kazakh (and vice versa), various errors may occur, since the Kazakh language is dierent from other languages, and has special characteristics. To compare the results, an empirical method was used, namely, monitoring and testing the translation results of machine translation systems. Considering the results of statistical methods, the rule-based and neural networks based methods in machine translations were also analyzed. The practical signicance of the study lies in the development of recommendations for the identication and elimination of errors when editing the results of MT. The scientic signicance of the study lies in the fact that for the rst time errors and inaccuracies arising from machine translation of the Kazakh language have been systematized. The assessment of the quality of MT is also presented. The research carried out in this article will be used for the post-editing problem in machine translation.