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In March 2023, the Japan-Korea summit was held in Japan, and in May, the Japan-Korea summit was held in South Korea. It was the first summit in 12 years and attracted a lot of attention. Major broadcasting stations broadcast the summit live with simultaneous interpretation. This article will examine how the titles of the leaders of the two countries were interpreted in the simultaneous interpretations broadcast by each station. All interpretation is important, but interpreting the speech of a head of state is even more so, as each word the interpreter chooses can lead to diplomatic issues. In this paper, we focus on the suffix ‘nim’. Chapter 2 examines the validity of the research topic by reviewing previous studies. Chapter 3 examines the presidential speeches, and Chapter 4 examines whether a certain norm can be identified in the use of suffixes in the simultaneous interpretation of joint press conference speeches. Chapter 5 examines the position of the presidential office, and finally, I make recommendations on the use of suffixes in Korean-Japanese simultaneous interpretation.

The present study analyzes undergraduate translation students’ work and discusses its implications. By identifying difficulties students face when beginning to study translation, the study aims to provide a platform for further discussion on translator education. It focuses on instances of language interference in student translations, discussing literature on language interference and translator education. The study highlights the importance of teaching students about the risks of language interference in translation, even in the age of AI, and reviews the types of language interference suggested in the literature. It examines students’ translations of a text about the bankruptcy of Silicon Valley Bank and its impact on the stock market, describing cases where students fell into language interference. The study established criteria for classifying language interference, analyzed translations based on these criteria, and used student journal analysis to derive educational implications. It is hoped that these findings will lay the groundwork for future research into the long-term development of translation competence, and will serve as the basis for a semi-longitudinal study comparing undergraduate students’ translations from their first to fourth years. Ultimately, this research contributes to identifying the characteristics of student translations and pinpointing areas where translation education should focus in order to enhance translation competence.

This study examines the differences in the frequency and intensity of profanity usage and translation strategies between the Korean filmGirl Cops and the American film Charlie’s Angels 3. Through this comparative analysis, it aims to demonstrate that profanity translation is a complex process that transcends linguistic transformation, reflecting each culture’s social norms and audience preferences. The results indicate that in Girl Cops, profanity is predominantly used in action scenes to emphasize tension and conflict. However, in the translation, such profanities were often omitted or softened, reflecting strategic choices to align with target audience preferences and rating standards. In contrast, Charlie’s Angels 3 restricts the overall profanity use more strictly but retains or intensifies language in certain scenes to enhance emotional expression. This study emphasizes the importance of analyzing profanity translation as a cultural and social practice requiring careful consideration of audience expectations and societal norms. By focusing on two films with different cultural contexts and rating systems, this research provides valuable insights into how profanity is used and translated in audiovisual media. It is also hoped that this study will contribute to the standardization of profanity translation and consistency in rating standards.

In this paper, the results of the certification examination for court interpreters were analyzed to investigate how different evaluation criteria impact overall scores based on the examinees' score ranges. The findings revealed that, regardless of the interpreting mode, examinees who scored below 70 points (failing) were most significantly affected by the fluency of the target language. In dialogue interpreting, low target language fluency resulted in poor outcomes, independent of other factors. Once target language fluency was achieved, faithfulness to the original message became the primary factor influencing the results. In consecutive interpreting, note-taking proficiency was found to have a substantial impact on performance. Unlike dialogue interpreting, where note-taking was not required, candidates who were less familiar with the note-taking process tended to struggle, even with target language fluency. This suggests that note-taking proficiency played a critical role in consecutive interpreting. For sight translation, the ability to naturally convey specialized terms and expressions determined pass or fail outcomes. Although sight translation does not rely heavily on memory, faithfulness to the content still played a significant role in the success of candidates scoring above 70 points, indicating frequent omissions or mistranslations among lower-scoring candidates.

This study aims to compare the performance of various AI-based translators in handling rhetorical devices deployed to enhance the persuasive effect of speeches. Different presidents employ their preferred rhetorical techniques, among whom French President Emanuel Macron is known for frequent use of repetition. For example, in his 2024 New Year's address, Macron utilized several rhetorical devices (anaphora, antithesis, anadiplosis, amplification), including repetition at the sentence structure level. Since translation should take into account the text's type and function, it is crucial that these rhetorical elements, which amplify the speech’s persuasive function, are accurately conveyed, even in machine translations. In this context, this study analyzes Macron's 2024 New Year's speech, focusing on phrases employing sentence-level rhetoric. These phrases were translated from French to Korean using three artificial neural network-based translators (Google, DeepL, and Papago) and a generative AI (ChatGPT) to assess their ability to handle rhetorical devices. The analysis revealed that the machine translators varied in their effectiveness at processing rhetorical elements, with ChatGPT performing the best, followed by DeepL. ChatGPT produced fewer semantic errors, even when omitting certain words or expressions, and generally handled rhetorical translations more effectively. However, most translators struggled with longer sentences containing multiple rhetorical devices, such as omissions.

This essay provides a multifaceted analysis of the evolving landscape of translation and the changing role of human translators in the age of Generative AI. The first chapter introduces key issues by exploring how AI has replicated and surpassed human cognitive capabilities. The second chapter examines the rise of AI-driven automation in the context of Karl Marx’s anti-capitalist critique, highlighting its impact on the depreciation of human translation labor. The third chapter draws on Albert Camus’s existentialist view of Sisyphus to put an optimistic interpretation on the act of translation. The fourth chapter adopts a critical posthumanist framework to discuss the wider implications of the translation network increasingly dominated by AI agents (machine translators). The fifth chapter explores the potential of a “post-translation” or “post-translator” perspective, focusing on emerging phenomena such as “flattening” and “paratranslation.” The sixth chapter delves deeply into the cyborgization of human-machine translation and its ethical implications. Specifically, this chapter envisions “translation trademark symbols” (e.g., TRANSLATION™, TRANSLATION®) and discusses how Lawrence Venuti’s notion of visibility gains renewed significance in the AI era.

As a globally popular TV sitcom, Friends has been translated for diverse audiences, including viewers in China. When comparing translations from two different platforms, released with a time gap of ten years, significant differences can be observed in the translation of gender-related expressions. The translation of Friends on Sohu.com, released in 2012, and on Bilibili, produced in 2022, show notable changes in how gender-related expressions are conveyed. This study analyzes these differences using Fairclough’s three-stage model of critical discourse analysis to demonstrate how the variations reflect the political and societal contexts of their respective time periods. Fairclough’s framework, though commonly applied to news, speeches, and other social texts, is rarely used to analyze entertainment media, such as television shows. By applying this model to Friends, this study contributes to the understanding of how translations of entertainment content are shaped by their socio-political environment.

This study explores the notion of translator style through a corpus-based analysis of non-literary translation, an area less frequently scrutinized compared to literary translation. It addresses the gap in research by focusing on howtranslators manage sentence segmentation during the translation process. This is an aspect often overlooked by prior studies which have traditionally prioritized lexical characteristics within sentences. The corpus comprises translations fromthree seasoned translators of English business books into Korean, supported by interviews that delve into their translation choices. Results reveal distinct stylistic patterns in handling sentence structure, suggesting that such strategies can significantlymark a translator’s style. Among three translators, the one who stated he could freely alter the segmentation of sentences in the original text was found to split sentences more frequently in his actual translations than the other two, who believed that the original sentence segmentation should not be altered. This difference was statistically significant. The findings in this study are meaningful as they were derived fromthe corpora that were meticulously designed tominimize external influences fromother agents such as editors. This study not only extends the understanding of translator style but also suggests practical implications for identifying individual translator's stylistic signatures in non-literary texts.

This study examines the characteristics and quality of machine translation (MT) for named entities (NEs). We first provided an overview of the underlying mechanisms and technical obstacles involved in NE translation, based on previous studies in this field to understand the challenges that MTs may encounter when translating NEs. Based on these theoretical considerations, we proposed three hypotheses regarding potential NE-related translation problems and error types: (1) MTs may struggle to translate NEs consistently; (2) MTs often fail to differentiate proper nouns from common nouns; and (3) without sufficient contextual support, low-frequency NEs may be translated incorrectly, resulting in non-words or semantically unrelated terms. We performed a statistical analysis of 120 translations produced by two standard MT systems (Google Translate and Papago) and two generative artificial intelligence models (ChatGPT 3.5 and ClovaX) to test these hypotheses. The results revealed that (1) consistency errors occurred in 4.21%–26%of all NE translations, (2) 19.55%–50.34% of proper nouns that could be confused with common nouns were incorrectly translated as such, and (3) 31.31%–35.72%of low-frequency NEs lacking sufficient context were mistranslated.