Jun 2026· Journal of Universal Science Research· Vol 4, pp. 121-131· 0 citations
TL;DR
The findings indicate that artificial intelligence can function as an effective auxiliary tool in translation, but human translators and post-editing remain essential in literary, academic, legal, medical and journalistic texts.
Abstract
This article analyzes linguistic and stylistic problems that arise in translation processes in the age of artificial intelligence, particularly through neural machine translation and large language models. The study acknowledges the advantages of AI-assisted translation, including speed, multilingual processing and the production of preliminary drafts. However, the main focus is placed on semantic ambiguity, contextual misinterpretation, literal rendering of idiomatic expressions, inconsistency in terminology, stylistic neutralization and the loss of cultural connotations. The article proposes an analytical model for assessing translation quality based on linguistic, stylistic and pragmatic criteria. The findings indicate that artificial intelligence can function as an effective auxiliary tool in translation, but human translators and post-editing remain essential in literary, academic, legal, medical and journalistic texts
The work highlights the need to take into account the stylistic and semantic features of poetic discourse in automated translation and suggests ways to improve machine translation algorithms to more accurately convey the artistic and emotional nuances of poetry.
D.T. Teshebaeva· Vestnik of the Kyrgyz-Russia...· 0 citations
This study concludes that while all AI tools can transfer denotative meaning, generative models (LLMs) are superior in applying high-level translation techniques necessary for maintaining emotional nuance, discourse cohesion, and literary appeal.
The results indicate that these AI tools are highly effective at the lexical and syntactic levels, but also reveal limitations in the domain of phraseology, that is, in the translation of stylistically marked linguistic units.
Magdalena Duvnjak, V. Fedorov, Miloš Pupavac· SINTEZA· 0 citations
The study concludes that terminological consistency should be considered as a separate dimension of translation quality and emphasizes the importance of terminology control and human post-editing in AI-assisted political translation.
Osama Bala· (Faculty of Arts Journal) مج...· 0 citations
The paper argues that NLP should operate as an interpretive assistant rather than an autonomous literary translator in translating Iraqi poetry into English, and proposes a culturally aware, human-in-the-loop framework for supporting literary translation.
Whaj Mneer Esmail· Iraqi Literary and Cultural...· 0 citations
The results show that LLMs and Google Translate consistently outperform specialized MT systems in terms of fluency, meaning preservation, and lexical-thematic alignment.
Beatriz Ribeiro Borges, P. H. R. Gabriel, E. Faria· International Journal of Dat...· 0 citations
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