Earticle

Social media has become an important online field in which professional identity construction occurs(Gal et al., 2016). This study aims to understand how interpreters are perceived and represented on the video-sharing website YouTube (www.youtube.com). Using Selenium, a Python library, the title and description of all 298 videos searched with the keyword “tongyeoksa”(meaning “interpreter” in Korean) were scraped. Keyword analysis, co-occurrence network analysis and LDA topic modeling analysis were employed to derive insights from the scraped data set. A qualitative content analysis was performed to complement the result of analysis. Through the analysis, the study reveals that the main topics of ‘interpreter-related’ YouTube videos are “Occupation and English Learning”, “Interpreters under the Media Spotlight”, “Sign Language Interpretation and Certificate”, “Female Sports Interpreter and Appearance”, and “Lectures and Awareness-raising”. Perception of interpreters in general showed an association with ‘foreign language skills’, ‘foreign language learning’, and ‘the growing popularity of Korean cultural content overseas’. On the other hand, ‘certificate’ and ‘awareness-raising about human rights of the socially-underprivileged’ appeared as main topics in the online discourse of sign language interpreters while ‘femininity’ and ‘appearance’ were highlighted in sports interpreters.

With the rise of alternative teaching methods, flipped learning has been growing in popularity across academic disciplines. Flipped learning is a pedagogical approach where traditional lectures are shifted outside the classroom, allowing more time for students to engage in student-centered learning and dynamic, group-based activities in an interactive learning environment to improve learning outcomes. This paper aims to develop and apply flipped learning lesson plans to a translation course to examine the feasibility of a flipped learning model in T&I classes. Participants numbered 17 first-semester graduate students enrolled in a Korean-English translation course at a graduate school of interpreting and translation in Korea. During the 13-week semester, a 9-week flipped learning approach was adopted. The flipped learning class activities were categorized into pre-class, in-class, and post-class based on previous literature. Findings from a post survey conducted at the end of the semester revealed the participants’ overall satisfaction with the flipped classroom approach. Students responded that small group discussion sessions held during class were particularly useful as they provided an opportunity to explore their understanding of various translation issues with their peers. The instructor’s course evaluation scores were also positive. The results and pedagogical implications are discussed based on students responses.

In this study, we conducted a survey asking undergraduate students majoring in translation about their perceptions of machine translation (MT). The respondents were 153 students in a translation department at Hankuk University of Foreign Studies in South Korea. The questionnaire contained thirty-six closed-ended questions and three open-ended questions. The main focus of the survey was (1) how the students had used MT output to further their learning of translation and English as a foreign language, (2) what they thought about their curriculum in general and MT-related courses in particular, and (3) what effects they expected technology advancement to have on their future career and the status of translators. The responses show that many students actively use free online MT services and take a fairly positive view of the quality of MT. The students feel that MT-related education should be expanded to meet the changing needs, with careful attention given to the current curricular framework. They also mention that MT training will likely improve their career prospects and it is thus necessary to acquire first-hand knowledge of technological aspects of translation. Findings of this study could be used as reference material to improve curricular programs for undergraduate students who major in translation or lesser-known foreign languages.

This paper addresses the quality of Korean-English legal translation outputs generated by three neural machine translation engines, namely NMT1, NMT2 and NMT3. NMT1 and NMT2 are widely available multilingual generic machine translation engines, whereas NMT3 is a custom machine translation engine for legal translation. In both automatic and human evaluations of the three engines’ English translations of Korean statutes, the custom engine outperformed the other two NMTs. BLEU and METEOR scores revealed that NMT3’s output was more similar to human reference translation. Human evaluation results confirmed NMT3’s strong performance, outperforming the generic engines in accuracy and fluency while underperforming in terminology. However, further analysis revealed that NMT3 was superior in handling terms comprising compound nouns and sentences over 25 words. Although the custom engine’s performance still requires substantial human involvement for quality translation, it showed a potential for the legal domain, demonstrating human parity in short sentences. The growing demand for speedy translation under budget constraints calls for further research on technology-based translation tools and human-computer interaction for legal translation.

As picture books combine visual and verbal means of expression, picture book translators recreate words with the help of visual signs. This study examines translation shifts for multimodality such as words signs and visual signs in picture books, and describes translation shifts from the perspective of transcreation. For this purpose, this paper defines transcreation strategies as “verbalization of visual signs” - addition of verbal signs to target texts or transformation of visual signs in source texts – modifying Gottlieb‘s concept of verbalizing translation of multimodal text translation. The verbalization of visual signs reveal three major transcreation strategies: (1) “the verbalization of fact” that truthfully describes the visual signs of source texts to the words of target texts, (2) “the verbalization of emotion” that adds feelings of the visual signs of source texts to the words of target texts, (3) “the verbalization of auditory effect” and “the verbalization of visual effect” that use onomatopoeia and mimetic words. As a case study, three Chinese picture books and their Korean translations were chosen. There are transcreation strategies for multimodality, “the verbalization of visual signs” in three Korean translations. This has shown that translators should consider the interaction with other modes of the multimodal text such as words, images and sounds, and use their creativity to meet the demand and expectation of new readers.

While text difficulty is one of the critical considerations in developing and selecting materials for interpreter training, its assessment is a challenging task due to the complexities involved in analyzing a large number of text characteristics. The recent developments in automated text analysis methods and tools are expected to alleviate the burden of individual teachers and students assessing source text difficulty by aiding their decision making process with the immediate provision of data on the objective and quantifiable text dimensions. This study presents three cases of applying automated assessment of source text difficulty based on the five Text Easability Principal Component Scores provided by Coh-Metrix, a widely-used automated tool for multilevel analyses of text characteristics. For the purpose of the study, source texts used for interpreter training in Korea and China were sampled to conduct text difficulty assessment with Coh-Metrix measures and its visualization tool. The study discusses the potential benefits of automated analysis of multidimensional text difficulty for selecting the appropriate materials for effective interpreter training.

The purpose of this study is to present Machine Translation (MT) metalanguage learning activities and to examine whether the degree of metalanguage utilization shown by undergraduate students majoring in translation is related to their explicit knowledge, and their ability to identify and solve translation problems. Metalanguage helps learners to learn foreign languages by activating the metalanguage knowledge they have about their native language and their ability to explain specific language phenomena or translation problems. Unlike the previous undergraduate machine translation education research focused on post-editing, this study attempts to use machine translation as a tool for translation learning with the purpose of promoting understanding and knowledge of translation and explaining theoretical approaches to translation problems. Using the machine translation result of the novel Pachinko, students conducted the following learning activities with “Translation Problem Judgment Tests”: 1) Understand the translation problems, 2) Indicate the translation problems, and 3) Explain and correct the translation problems. The analysis found that although the use of metalanguage was active, there was a case where the translation problem was not accurately identified and analyzed. This meant that the two sub-categories of explicit knowledge, metalanguage and analyzed knowledge, were not highly correlated. On the other hand, the higher the frequency of using the metalanguage, the higher the explicit knowledge needed to explain the translation problem. Taken together, these results suggest that meta-linguistic education enhances students' awareness of translation and ultimately helps expand explicit knowledge. The findings of this research have significant implications because they show that metalanguage learning activities using machine translation in undergraduate translation education can help students increase their explicit knowledge of translation and extend their analytical skills.

This study explores the possibility that translators who have translated many works may develop their own translation styles rather than simply following the stylistic features of the source text. By examining the translation of Hwang Sun-won's concise literary style by two different translators, this study aims to identify the presence and aspects of their stylistic choices. An exploratory and stylometric approach was used to analyze a parallel corpus of 29 short stories by Hwang Sun-won and their translations by Bruce and Ju-chan Fulton and Edward W. Poitras, along with a corresponding reference corpus, at the lexical, syntactic, and textual levels, using stylistic markers such as STTR, average sentence length, syntactic complexity, readability, and document similarity. The results indicate that both the author's and the translators' styles contribute to the stylistic formation of translated texts, and the degree to which a translator's unique style is evident varies depending on the stylistic marker and the translator. These findings highlight the significant influence of stylistic choices made by translators on the final translated text, and emphasize the importance of considering both author's and translator's styles in translation production and analysis.