KJC Korea
Journal Central

This article explores the relationship between source and target text in museum audio description, along with its guidelines, and the nature of audio narration. The audio descriptions of Picasso’s works at MoMA, Tate, and MMCA are analyzed, revealing the following findings: MoMA’s audio description of “Les Demoiselles d’Avignon” (1907) effectively provides an objective and neutral description. Tate’s audio description of “Three Dancers” (1925) includes notable elements of audio narration, delving into character portrayal and addressing the “why” aspect. MMCA’s audio description of “Goat’s Head” (1952) and “Jacqueline with the Easel” (1956) incorporates the script specifically designed for the non-blind, highlighting the potential for combining audio guides and audio descriptions. This article is significant in its exploration of diverse possibilities in museum audio description and the potential for subjective audio narration for visual arts.

This study offers a comprehensive review of the Masters of Translation and Interpreting (MTI) programs in China, which show rapid expansion over the recent years, and analyzes and discusses their limitations and implications. The study first presents a general overview of the characteristics, types, and regional distribution of MTI programs in China. It then delves into the role of the GETI Committee, which oversees, manages, supervises, and evaluates China’s MTI programs, and provides in-depth examination of the MTI programs’ curricula, textbooks, and lesson plans. The analysis reveals that despite the original educational goals of MTI programs to cultivate “field-oriented translation and interpretation professionals,” their approach to translation and interpretation education remains primarily an extension of theoretical and foreign language education. Other studies on MTI programs underline the chronic issues of a theory-centered educational approach and the inadequate practical skills among graduates. The findings of this study suggest that these issues largely stem from a state-led, top-down curriculum design and an education model focused on the providers of education such as universities and instructors, rather than students.

This study aims to compare and analyze the Korean counterparts of Chinese political and diplomatic terms used in Chinese and Korean news media. Political and diplomatic terms are redefined as sensitive terms that may impact international relations or generate controversy. Following this definition, the study extracted political and diplomatic terms from Korean versions of Chinese media websites and classified them into two categories. It then examined the types of Korean counterparts and discussed the problems identified in their translations. Furthermore, the study suggested ways to improve the translation quality of political and diplomatic terms. The findings of the study revealed that a country’s political stance influences the selection of Korean equivalents, and differences were observed in the types of Korean counterparts used between Korean and Chinese news media. Moreover, various problems were identified in these Korean counterparts, such as incorrect use of punctuation, spelling errors, and inappropriate expressions. The study examined a variety of translation techniques that can effectively convey the nuanced meanings of political terms. It can provide valuable insights for future research on Chinese-Korean translation strategies for political and diplomatic terms.

This paper compares the quality of English-Korean patent translations by a patent-specific NMT engine trained using AutoML with the general Google Translate. The evaluation was based on both automatic and human evaluations of the Korean translations of 200 English patent sentences excerpted from a number of semiconductor patent gazettes. In automatic evaluation, BLEU scores showed that the patent-specific NMT engine significantly outperformed Google Translate. Human evaluation, carried out by sampling as well as error detection and correction analysis, confirmed the results of automatic evaluation, revealing that patent-specific NMT results were better than Google Translate results. In the error detection and correction analysis, Google Translate had more major errors than patent-specific NMT. Moreover, most errors in Google Translate were addressed in the patent-specific NMT, while errors in the patent-specific NMT still remained in Google Translate. In the sampling analysis, shorter sentences and longer sentences were sampled and analyzed. According to the results, both patent-specific NMT and Google Translate showed better performance in translating shorter sentences. In translating longer sentences, both translation engines exhibited accuracy-related errors and syntactic errors, though patent-specific NMT slightly outperformed Google Translate. Overall, translation results by patent-specific NMT showed better quality than those by Google Translate.

The advent of ChatGPT is making waves in various fields. The interactive AI can perform tasks commonly connected with human cognitive activities including playing games, analyzing medical data, and summarizing texts. In particular, the creativity of ChatGPT, which allows it to draw a painting or write a song, is a starting point for this study because translation is considered to be a creative work. Therefore, this study begins with the question of whether ChatGPT can translate a literary work, especially irony. Among the literary devices, irony is particularly difficult to translate because it requires a high level of complex perception and interpretation. Another reason why irony translation is difficult is that translators have difficulty choosing a translation strategy between the following two options: to literally translate irony to give readers a chance to find it, or to paraphrase irony to convey the intention of a writer. Until now, machine translation has had many difficulties not only in identifying irony, but also in translating it with an appropriate strategy. Therefore, this study aims to examine if ChatGPT can be utilized to translate irony. To answer the research question, we follow two processes. First, we take a source text and its target texts from human translation, machine translation using Google, and AI translation using ChatGPT, and then analyze them. The results show that ChatGPT understands and translates the meaning and intent of the source text more deeply than existing machine translation, even though the results were not as complete as the human translation. Secondly, we provide the AI with some information at the word, sentence, and context level so that it can understand cultural elements and contexts that include irony. In some cases, even when ChatGPT gets a clue, it does not understand or reflect the writer’s intention. However, it does actively utilize the provided information and the translation quality does improve. Therefore, our conclusion is three-fold. First, machine translation and AI translation can be used in different ways. Second, the interactive character of AI can be helpful to improve translation quality. And lastly, AI translation can be utilized to translate irony.