# The Task of Post-Editing Machine Translation for the Low-Resource Language
## 2 Materials and Methods  
### Post-Editing of Machine Translation for English-Kazakh and Russian-Kazakh Translation  
The task of post-editing machine translation is the focus of attention of researchers who are concerned with the development of automated translation systems. This problem becomes especially relevant for low-resource languages, such as Kazakh, Kyrgyz, Uzbek, and others [28]. The Kazakh language is characterized by an extensive morphology, which makes the task of machine translation difficult. Errors in determining the basis of a word or in morphemes can lead to significant errors in translation. In this context, machine translation post-editing (MTPE) often focuses on correcting morphological errors.  
Traditional MTP systems based on statistical machine translation (SMT) were used in the early years of the development of translation technologies for the Kazakh language. Approaches to automatic post-editing of machine translation were initially developed on the basis of grammatical rules of the language. It all started with editing an error in a word, then the word forms that formulated the phrases, and then the sentences.  
We consider that the architecture of the MTP process for the Kazakh language can contain the following stages:1. Preparation of the source text. To do this, the initial input is scanned to check the correctness of the format and identify possible problems; after that, the source language is determined, and then the input text is divided into sentences or phrases.
2. Second item: The process of machine translation consists of tokenization, that is, splitting sentences into separate words or tokens, morphological analysis, the determination of morphological features of the language, a neural model, which is used by a trained MT model (for example, based on the transformer architecture) for the initial translation, and detokenization, that is, the conversion of tokenized text back into a readable format.
3. The post-editing stage: the initial review of the MT output data is carried out for the presence of obvious errors. After that, if the main goal is a general understanding, the text undergoes light editing, that is, only obvious errors are corrected. And, if the goal is a high-quality translation, the text undergoes complete editing and all kinds of errors, stylistic, grammatical, lexical, and semantic, are edited. The choice between light and full post-editing usually depends on the purpose of the translation, the project budget, and quality requirements.
4. Adaptive reverse cycle: corrections made during post-editing are returned back to the MP system to improve future translations. This stage is optional and depends on the availability of adaptive capabilities of the MT system.
5. Output data and verification: quality control is carried out, or rather, automatic checks for the presence of untranslated segments, inconsistencies, or problems with the format. The final review, the last stage, is performed to make sure that the translation meets the required quality standards. At the very end, the result is provided in the form of a ready translation and is output in the required format or medium. Figure 2 shows the general architecture of post-editing for the low-resource language.  
This architecture provides a sequential process from input to output, detailing each stage involved in the post-editing processes for the Kazakh and Uzbek languages. The post-editing module itself is divided into two levels, which are responsible for easy post-editing, that is, for making small changes to the machine translation text. Full post-editing carries out a detailed correction of possible synthetic and lexical errors of machine translation [29].  
Further, descriptions of the processes of the main levels of the machine translation post-editing system will be presented.