Tolegenova A.2024-12-192024-12-192022https://repository.sdu.edu.kz/handle/123456789/1585The amount of complicated documents and texts has increased exponentially in recent years, necessitating a deeper understanding of machine learning technologies in order to effectively identify texts in numerous applications. Text normalization is one of the best decisions. It is the reduction of all words of the text to the original form. This paper investigates a layered strategy for fixing mistakes in Kazakh language literature downloaded from the Internet. This work is devoted to the study of automatic systems for checking the spelling of the Kazakh language using natural language processing tasks. Currently, most of these types of machines are designed for English, and few are processed for the Kazakh language. The paper discusses the methodology for evaluating automatic spelling checkers and error correction, developed by the author. A description of the selected systems is given. The main goal is to validate the use of n gram for agglutinative languages. On the basis of the study, the best system of use is distinguished, between the n gram and Symspell.ennatural language, processing pell algorithm, text normalization, spell correction, n-gram model, SymSOther