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With the recent significant advancements in AI technology, the internal and external environment of interpretation education is rapidly changing. In particular, the generative AI tool ChatGPT-4 has shown a remarkable improvement compared to previous versions. Given these developments, this study aims to explore ways to integrate AI technology into professional interpretation education. To this end, the study will first analyze the performance of AI interpreters at present and compile recent AI-based interpretation research published in academia. Using these observations, the study will explore the feasibility of applying AI tools to professional interpretation practice. Second, the study seeks to provide opportunities for interpretation professionals to leverage these technological advancements to enhance their capabilities by proposing methods to integrate AI technology into future interpretation education programs. In doing so, the study aims to offer an understanding of how AI technology can complement and expand human linguistic and non-linguistic abilities and provide important insights into the future development direction of the interpretation field.

Generative AI has revolutionized machine translation (MT) by enabling customizable outputs through prompt engineering. Unlike traditional neural machine translation (NMT) systems such as Google Translate and DeepL, which rely on predefined translation patterns, models like GPT-4 allow users to refine translation quality through different prompting strategies. This study examines the impact of Zero-shot, Few-shot, Style-specific, and Step-by-step prompting on translation quality and evaluates the effectiveness of Auto Prompt Optimization (APO) in further enhancing performance. Using GPT-4, translations were conducted for Korean-to-English, Japanese, Chinese (Ko→En, Ja, Zh) language pairs. The study assessed BLEU, TER, and COMET scores to measure accuracy, fluency, and semantic consistency. Results show that Few-shot and Step-by-step prompting significantly improve translation quality, while APO further enhances BLEU scores and reduces TER values across all prompting types. Findings also indicate that prompt effectiveness varies by language pair, emphasizing the need for language-specific prompt strategies. This study provides empirical evidence of how prompt engineering influences AI translation quality and offers strategic guidelines for optimizing translation performance.

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.

In undergraduate interpreter training, students are more likely to encounter bilateral interpreting between two working languages than conference interpreting, either during their studies or future careers. However, dialogue interpreting classes often present challenges due to students' limited linguistic competence and lack of subject knowledge. To address these difficulties, this study explores how students use generative AI to create dialogue scripts for interpreting practice, focusing on prompt literacy, AI-generated text features, and learners' perceptions. Students worked in small groups to generate weekly dialogue scripts on assigned topics using ChatGPT. These scripts were then enacted in class as role-plays, with each student taking a participant's role. Spontaneous interpreting was performed by other students selected by the instructor. Each group submitted full logs of their prompts and AI-generated outputs weekly and completed a survey at the end of the semester. The findings indicate that students' prompting strategies generally aligned with expert techniques and improved over time. The generated scripts proved suitable as source texts for interpreting exercises, requiring only minor revisions. Furthermore, the dialogues displayed a strong sense of realismand authenticity, enhancing learner immersion and engagement. Overall, students responded positively to the use of ChatGPT in script preparation. This study highlights the pedagogical potential of generative AI in undergraduate interpreter education.

Onomatopoeia is a difficult constituent in translation because it has different characteristics which prevent source and target text readers from communicating each other. Most of target text readers are unable to have knowledge to understand connotations of the exotic onomatopoeia elements in the source text. Accordingly the translator has to be a mediator to bridge the gap in understanding onomatopoeic expressions and help the target text readers to share the equivalent connotations of them. The purpose of this paper is to examine the translation problems in translating Korean poetry texts into English ones by focusing on onomatopoeic expressions which appear in the translation process. This paper has shown that the poetic phrases of Korean related to onomatopoeic expressions are translated into those of English by various strategies, for example, paraphrase, substitution and omission which have active and diverse compensation mechanisms.

This study quantitatively examines stylistic differences between human and machine translation in literary texts. A parallel corpus was constructed from five source languages-German, Arabic, Indonesian, Japanese, and Chinese-each translated into Korean by professional human translators and two machine translation systems, Google Translate and Gemini. Using five machine learning algorithms (Decision Tree, Random Forest, XG-Boost, t-SNE, and PCA), we analyzed a range of stylometric features to determine the separability of human and machine outputs. Our results show that human and machine translations are highly distinguishable, with classification models achieving over 90%accuracy. Gemini’s stylistic profile aligned more closely with that of Google Translate than with human translators. The analysis revealed comma ratio as the strongest discriminator, followed by sentence count and pronoun ratio. These findings provide empirical evidence of a persistent stylistic gap between human and machine translation in the literary domain and identify specific linguistic features that mark this divide.

This paper introduces and explains the general concept of “cultural translation” put forward by Homi K. Bhabha. As opposed to the traditional concept of translation (simply put, a linguistic transfer or substitution), Bhabha’s translation is concerned with “negotiation between [hybrid] cultures” and “the condition and process of human migration.” This paradigmatic nature of cultural translation enables translation researchers to reflect on its four theoretical values. First and foremost, it helps Pierre Bourdieu’s field theory to better conceptualize the so-called translation field. Second, it fills some voids left by polysystem theory. Third, it intrinsically emphasizes the importance and relevance of a “top-down” translation. Fourth, its interdisciplinarity has great potential to extend the depth and breadth of translation studies.

This study examines the translation strategy of culturemes in the English subtitle of Parasite, a Korean movie by director Bong Joon-ho. The multi-award winning black comedy deals with the conflict between the rich and the poor, a topic which people in every culture can relate to. Together with the timely theme, the film’s English subtitle is considered to have contributed to its global success. This study shows that Darcy Paquet, the subtitle translator of Parasite, carefully chose the translation strategy working in close cooperation with the director. The interviews and press clips on the translator and the director revealed that they actively communicated on how to translate the local elements in the movie into English subtitle so that audiences in other cultures can easily understand the movie, which is the macro translation strategy. This paper categorized 22 culturemes in the movie into 5 groups and found out that 6 different tactics under 2 broad categories of conservation and substitution were used for translation. The analysis shows that although various tactics were used at the micro level, the subtitle as a whole worked in a way to enhance the understanding of foreign audiences, with the aim of domestication at the macro level.

This paper tries to analyse translation criticism on published books, using concept and sub-categories of translation norms. Analysed in this paper translation criticism divided into shcolars’ (but not in translation studies area) and general readers’. Translation norms as an analysing tool consist of 1) adequacy vs. acceptability, 2) translation policy, 3) directness 4) matricial norm 5) text-linguistic norm. Results are as follows: scholars’ criticism tends to focus on adequacy (accordance with source text culture), whereas general readers point out insufficient acceptability(accordance with source text culture); it seems that translation policy and directness are not the main concern in translation criticism; adequacy vs. acceptability norm is closely related with matricial and text-linguistic norm. The difference of scholars’ and general readers’ criticism tendency implies that different views possibly exist between various reader groups. This point needs further examination. Close relationship between adequacy vs. acceptability and matricial vs. text-linguistic norm also needs further research. The latter may be concrete basis for the former. It it is confirmed, we can make the analysing tool more simple. As for general readers, it is observed that readers, publishing companies and tranlators interact very actively on Internet sites. Although based on limited examples, this paper shows current state of translation criticism by Korean readers.

With the global spread of K-culture, original Korean musicals (K-musicals) are increasingly exported and supertitled for foreign audiences in Korea. As Chinese nationals form the largest group of foreign residents, and exports to China grow, the translation of Chinese supertitles is gaining importance. Yet research on this topic remains limited. This study examines the characteristics of Chinese lyrics and the challenges of translating Korean lyrics directly into Chinese. Focusing on the musical After Life, it proposes strategies that accommodate the unique demands of Chinese lyrics, which prioritize implicit and concise expression (xiěyìxìng), parallel structure (duìjù), rhyme, and repetition—elements often lost in direct translation. As specific strategeis, the translator proposes using sentence-final nouns, idioms, four-character expressions (chéngyǔ), and substitution and omission to achieve syllable alignment and structural cohesion. These techniques enhance rhythm and rhyme through restructured imagery and nominalization, while reinforcing poetic effects through repetition. Collectively, these strategies clarify and condense meaning while enriching lyrical subtlety. Though limited to one production and not easily generalizable to oral translation, this study offers concrete, experience-based subtitling strategies.