Moscow University Translation Studies Bulletin. 2026. 2.

The article presents a comprehensive analysis of the limitations of automatic speech translation systems in business communication and examines the risks associated with their use. The theoretical framework is based on translation studies, computational linguistics, cognitive approaches to translation, and psychology. The empirical basis includes comparative studies of machine translation quality, particularly error analysis of DeepL and Google Translate, as well as data from peer-reviewed studies across different language pairs. The study employs a combined methodology including comparative analysis, error classification, and quantitative assessment. It is established that modern neural network systems exhibit consistent lexico-semantic, syntactic, pragmatic, and culture-specific errors, which in business communication translate into legal, reputational, and financial risks. The key difference between professional interpreting and automatic speech translation lies in the human capacity for cognitively responsible interpretation — the integration of semantic, emotional, cultural, and strategic parameters of communication with awareness of the consequences of decisions made. To minimize risks, it is necessary to introduce post-editing standards, develop users’ machine translation literacy, and form hybrid models.

Object. The study addresses the complex linguacultural and typological challenges inherent in the artistic translation of Russian prose into Persian. It focuses on the translation of two stylistically distinct works: K.G. Paustovsky's "Snow" and V.V. Veresaev's "The Contest". The primary objective is to systematize the strategies used to overcome interlinguistic asymmetry when translating from a synthetic (Russian) to an analytical (Persian) language, while preserving the author's unique "idiostyle" and aesthetic impact.

Methods. The methodological framework integrates a comparative-typological approach with transformational analysis based on the theories of L.S. Barkhudarov and V.N. Komissarov. To identify practical translation difficulties, a linguistic experiment was conducted at Bojnourd University involving 28 senior Persian-speaking students. The qualitative and quantitative analysis of their translations served as the empirical basis for identifying interference errors and verifying the effectiveness of various translational transformations.

Findings. The analysis reveals that structural differences between the languages — such as word order (SOV in Persian vs. free order in Russian) and the absence of a case system in Persian — necessitate extensive grammatical restructuring. Key findings indicate that translating Paustovsky's lyrical prose requires sophisticated stylistic substitutions and syntactic compression to maintain "lyrical atmosphere." In contrast, Veresaev's realistic style demands pragmatic adaptation and lexical modulation to ensure ethical and psychological clarity for the Persian reader. The study provides a detailed account of specific adaptations, including the "explicitization" of historical contexts (e.g., the autumn of 1941) and the functional substitution of cultural symbols (e.g., replacing the "laurel wreath" with the Persian concept of "crown of glory"). It is shown that direct literal translation often leads to semantic lacunae, which must be filled through descriptive translation or modulation.

Conclusions. The research concludes that successful literary translation from Russian to Persian is a cognitive-hermeneutic process rather than a mere substitution of lexical units. Effective translation strategies are determined by both linguistic typology and the specific cultural codes of the target audience. The findings offer a significant contribution to the field of comparative linguistics and provide a scientific foundation for improving translation pedagogy in Iranian universities.

This article analyzes translation strategies and adaptive tools used in rendering texts from British periodicals. The primary tools employed in the study are the DeepL and Reverso Context platforms, which support semi-automatic translation workflows for both literary and journalistic texts. The aim of the study is to determine the most effective translation strategies for rendering wordplay in British tabloid newspapers through the integration of online platforms and traditional adaptive translation methods. The corpus analyzed in this study consists of texts published in The Observer and The Sun, which most clearly demonstrate key aspects of translation practice. The material includes headlines and articles published between 2019 and 2025, primarily from editorial sections. The methodological framework is based on adaptive and comprehensive translation approaches, focusing on text transformation with regard to cultural specifics, social realities, linguistic features, and journalistic style. When selecting translation strategies, the authors adopt a functionalist approach grounded in Skopos theory. The study identifies translation practices in literary and journalistic discourse based on the above-mentioned platforms, and clarifies approaches to linguistic creativity, glossing, searching, analysis, and interpretation of wordplay, as well as semi-automatic translation and post-editing for the development of terminology databases and the refinement of machine translation outputs using artificial intelligence tools. The authors conclude that further methodological development is required in modeling different types of discourse (publisher, journalist, and audience perspectives) in the translation process. In addition to online platforms, this requires supplementary adaptive translation tools, including post-editing, text deconstruction, case studies, and generalization.

The main positions of the unit to which the German machine-gunner belongs are somewhere behind him on the forward outpost. Here, in the deserted forest, he is completely alone — just him and a great deal of snow. The occasional rustle of snow falling from the trees is perceived by the soldier as the cautious, stifled breathing of a creeping enemy. Trying to suppress his fear, the sentry begins to sing Christmas carols — even though it is already February, and German Christmas is long past. Seeing the feldwebel hurrying towards him, the soldier stops singing and decides that now he will be shot for singing on guard duty. However, the feldwebel, who is no less afraid than the soldier of the invisible enemies lurking in the forest, does not connect the singing of Christmas carols with the sentry. To him, it seems like a hallucination and that he is going mad. Running up to the soldier, the feldwebel grabs hold of him and, glancing around nervously, hastily confides his fears. The plot of the story is based on the author’s personal experiences: as a Wehrmacht soldier, he once found himself, against his will, alone in a snowy Russian forest near Tver in the winter of 1941–1942. The article presents fragments of translations of the story into Russian and English, undertaken by translators of varying skill levels and executed at different levels of mastery.

The purpose of this article is to examine attitudes toward the Russian language among representatives of the second generation of the first wave of Russian emigration in France (1991–1992) and Canada (1995, 1998). The material is based on interview recordings published in written form in 2004, which subsequently formed the basis for the creation of the electronic corpus Russian Emigrant Speech at the Laboratory of General and Computational Lexicography, Faculty of Philology, Lomonosov Moscow State University. The study reveals a strong and well-established connection between the preservation of the native language and immersion in the history and culture of the homeland among representatives of the second generation. It is evident that without the establishment of communication centers, the development of specialized homeland-studies literature, and the strengthening of cultural ties, the Russian language outside Russia has limited prospects for preservation and large-scale transmission.

There are a lot of different words meaning ‘love’ or ‘to love’ in Japanese language, including 愛する ‘ai-suru’, 恋する ‘koi-suru’, 好き ‘suki’, 憧れる ‘akogareru’, etc. However, in order to use each of these words correctly and in a proper way, it is necessary to understand the nuances that determine the usage of words in a context given. One of the main problems of the interpreter from Japanese to any other language is one of the basic features of Japanese communication which is the so-called ‘non-speaking’. This characteristic can be described as a constant manner of not talking directly on a matter which the speaker is most concerned about. Speaker’s counterpart is expected to either understand him without talking at all, basing solely on the context of communication, or by guessing his true feelings and intentions by ‘reading between the lines’. So, the different lexical shades of the words used to signify ‘love’ combined with the Japanese traditional way of indirect expression of thoughts and feelings both make the task of a translator really challenging. Firstly, he has to correctly interpret anime characters’ speech, being guided also by one’s own knowledge of Japanese cultural characteristics. Only after that can he properly convey the main meaning of the expression used into Russian or any other language. The aim of this article is to identify and formulate the most common ways of expressing love in anime and also to analyze, what do they actually mean and in what situations they can (or cannot) be used.

Due to the long historical development of Chinese language and culture, culture-specific lexical items have undergone processes of historical consolidation, geographical influence, social formation, and religious shaping, gradually becoming distinctive cultural symbols that carry rich connotations and play a significant role in intercultural communication. Culture-specific items can be conditionally divided into five categories: ecological, material, social, religious, and linguistic. They are widely used in literary texts and pose challenges for translation.

The purpose of this study is to identify and analyze strategies for rendering Chinese culture-specific vocabulary in literary texts in intercultural communication contexts, as well as to evaluate their effectiveness based on Russian translations of Mo Yan's works. The following methods are employed: classificatory analysis, comparative-contrastive analysis, translation strategy analysis, and theoretical analysis.

Results. The analysis revealed that the most effective approach to rendering culture-specific vocabulary is a combination of strategies, including literal translation, literal translation with annotations, paraphrasing, transcription, and neologism formation. The findings confirm the importance of flexibly combining foreignization and domestication strategies.

Conclusion. Culture-specific vocabulary in literary texts is fundamentally translatable. The success of translation depends on the adaptive selection of strategies, taking into account the type of cultural reference, context, and target audience reception. Translation thus serves as an effective tool for intercultural dialogue, revealing unique cultural meanings.

Object: this study presents a comparative analysis of the quality of machine translation (MT) produced by three leading systems (Google Translate, Yandex Translate, DeepL) across three specialized domains (medicine, law, and news articles). The analysis employs an original multi-agent approach based on the YandexGPT large language model.

Methods: the research material comprises 60 English-language texts (20 per domain), each translated by the three MT engines, resulting in a total of 180 translations for evaluation. A system of six virtual expert agents powered by YandexGPT was developed for assessment: a linguist, a semanticist, a terminologist, a pragmatist, a cultural adaptor, and a domain-specific expert (medical/legal/media discourse). Each agent evaluated translations on a 10-point scale. An agent-moderator then synthesized these individual assessments to produce a final score. Statistical analysis included ANOVA, Student's t-test, and Pearson/Spearman correlation analysis.

Findings: DeepL achieved the highest overall score (8.57±0.69), demonstrating particular strength in the legal domain (8.47). Google Translate unexpectedly excelled in the medical domain (8.80) and also led in media texts (8.59). Yandex Translate ranked third across all domains, exhibiting the highest score variability (7.91±1.06) and critical errors in legal translations (minimum score of 5.0). Statistically significant differences were found between the MT engines (p < 0.05). Correlation analysis of agent scores revealed high consistency between the linguist and semanticist (r = 0.82).

Conclusions: the proposed multi-agent approach provides explainable, multi-aspect evaluations. DeepL emerges as a versatile leader, particularly for legal translation; Google is preferable for medical and media texts; Yandex requires further development for specialized domains. These findings can inform post-editing strategies and guide the selection of MT systems for professional tasks.

Russian literary "speaking names" constitute a special type of proper names whose internal form and word-formation motivation serve characterological and evaluative functions, shaping both the literary image and the author's perspective. In Chinese translation, the phonetic form of anthroponyms is usually preserved, while their semantic and expressive potential is often reduced. The aim of this article is to identify the features of Chinese translation practice in rendering literary anthroponyms and to propose a strategy that preserves not only their phonetic form but also their semantic and cultural significance. A comparison of translations of anthroponyms in four Chinese versions of Gogol's Dead Souls, spanning more than 80 years of translation practice, reveals that transcription dominates the Russian — Chinese translation tradition as a means of foreignizing names in the target language. At the same time, an analysis of translations of individual "speaking names" proves that in Chinese there are cases where both the semantics of the names and their phonetic form are preserved. Based on these findings and on the functional-pragmatic features of anthroponyms, the article proposes a strategy of "semantic transcription" aimed at maintaining both the phonetic features and the semantic content of Russian "speaking names" in translation into Chinese. Testing the strategy on speaking names from Anton P. Chekhov's short stories shows that, while preserving the phonetic recognizability of the original names, semantic transcription activates the semantic potential of anthroponyms and aligns their sound with their meaning. The results are valuable both theoretically and practically. Theoretically, they expand the translation model from alphabetic to logographic languages, taking the latter's specific features into account. Practically, the study relies on an extensive illustrative corpus, and the proposed strategy is tested on "new" material not previously used in the framework of this approach.