CAT tools for the translation of Chinese texts
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Svitlana Virotchenko , Victoria Molotok

CAT tools for the translation of Chinese texts

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Introduction

Cat tools for the translation of chinese texts. Explore the effectiveness, challenges, and benefits of CAT tools for translating Chinese texts, considering linguistic complexities and cultural nuances. Boost speed and consistency with technological competence.

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Abstract

The article provides a comprehensive analysis of Computer-Assisted Translation (CAT) tools used in translating Chinese-language texts, taking into account the rapid digitalization of translation practices and the growing importance of technological support in the translator’s workflow. The problem is defined by the significant typological distance between Chinese and Ukrainian, the specifics of the Chinese grammatical and morphological system, the logographic writing, and the abundance of culturally marked elements that complicate automated processing. The aim of the study is to identify the capabilities, limitations, and overall effectiveness of CAT tools in translating Chinese texts of various styles and genres. The research methodology includes stylistic analysis, linguistic comparison, evaluation of machine-assisted translation quality, and analysis of  translator productivity when using translation memories, terminology databases, and integrated machine translation modules. The results demonstrate that CAT systems increase translation speed by 30–50%, ensure terminological consistency, and facilitate the handling of large text corpora; however, their efficiency decreases when translating idioms, chengyu, neologisms, and topic–comment sentence structures. Special attention is paid to segmentation issues, the rendering of aspectual and temporal meanings, adaptation of classifiers, and the transmission of context-dependent semantics. The conclusions emphasize that the successful use of CAT technologies in Chinese–Ukrainian translation requires a combination of technological competence and deep linguistic and cultural knowledge, along with continuous updating of linguistic resources and critical evaluation of automated suggestions.



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