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This study quantitatively analyzes the correlation between the Japanese response marker naruhodo and accompanying nonverbal behavior, specifically nodding, using a multimedia corpus. While previous research has mainly focused on other response markers such as soudesune, the interaction between naruhodo and nonverbal cues remains insufficiently explored. The main findings are as follows. First, naruhodo was primarily used by interviewers and moderators, indicating that the speaker’s role in the broadcast had a greater impact on its usage than factors such as age or gender. Second, in two-thirds of the naruhodo occurrences, it co-occurred with nodding behavior, especially when the preceding utterance reflected the speaker’s subjective opinion. Third, nodding rates and response types varied depending on the follow-up utterance, with two main patterns observed—continued attentive listening and confirmation requests—and nodding before a confirmation request tended to amplify explicit agreement. These findings suggest that linguistic and nonverbal elements function complementarily and highlight the need for theoretical and methodological expansion in multimodal interaction research.

This study examines the phenomenon of backtracking in English sentence processing from syntactic, semantic, and cognitive perspectives. It explores how adverbial clause type, tense combination, information structure, and collocational relations affect the degree of backtracking, with special attention to adverbial clauses such as ‘after’, ‘before’, ‘when’, ‘while’, and the ‘not A until B’ construction. Experimental analysis demonstrates that structural complexity, information focus, and (non-)collocational relationships between adverbial clause transitive verbs and main clause subjects are key factors determining backtracking strength and frequency. Longer clause structures and repeated tenses intensify the need for information reanalysis, thereby increasing backtracking effects. L2 learners often fail to backtrack in temporarily ambiguous sentences, leading to lower comprehension than L1 speakers. L2 learners need focused instruction and practice regarding backtracking. By using generative AI tools like ChatGPT 4.1, this study opens new possibilities for research in language processing and pedagogy.

This study investigates the sentence-final particle zán (咱) in The Romance of the Western Chamber (Xīxiāngjì 『西廂記』), focusing on its pragmatic functions and distribution. The analysis demonstrates that zán fulfills four modal roles: imperative, hortative, declarative, and requestive. In imperative contexts, it conveys commands directed at the addressee; in hortative contexts, it expresses polite proposals for joint action; in declarative contexts, it emphasizes or articulates the speaker’s judgment, intention, or resolution; and in requestive contexts, it demands the addressee’s action without implying collective participation. Unlike its primary function in Modern Chinese, where zán denotes first-person reference, in Xīxiāngjì it occurs predominantly in sentence-final position to signal modal nuances. A frequency analysis records 5 imperative, 4 hortative, 10 declarative, and 7 requestive instances. These findings indicate that zá (咱) in Yuan-dynasty drama carried a wider range of pragmatic functions than in later stages of Chinese, offering valuable insights into the historical evolution of sentence-final particles.

This study aims to investigate how Korean language learners from Chinese, Japanese, and English backgrounds utilize epistemic modality markers. Data from the National Institute of Korean Language's Corpus of Korean Learners is analyzed to identify patterns. Overall modality marker usage did not differ substantially across groups, but all learners used epistemic modality markers more in written than spoken contexts. In speech, learners shifted from certainty to probability markers showing a preference for less commitment. Native language differences as well as sociolinguistic and cultural factors significantly impacted modality usage by learners. In conclusion, this research deepens our understanding of Korean second language acquisition, highlighting L1 influence, pedagogical factors, and sociopragmatic considerations in learner language development.

This study compares the results of English open-ended writing assignments completed by 21 university students using two machine translation tools, Papago and ChatGPT. A survey was also conducted to examine their perceived usefulness and differences. To investigate the impact of English proficiency, participants are divided into two groups based on their TOEIC scores: above 600 and below 600. The analysis reveals that in the Papago-based writing tasks, there are noticeable differences in grammar and vocabulary usage between the two groups, while the results for content, structure, and mechanics are similar. In contrast, for the ChatGPT- based writing tasks, although the below-600 group uses prompts more frequently, the quality of their writing outcomes is similar to that of the above-600 group. This suggests that the quality of ChatGPT outputs depends more on the content of the prompts than on their frequency of use, and is largely unrelated to English proficiency. Survey results show that both groups raise concerns about overreliance on ChatGPT, including ethical issues and the potential decline in critical thinking and English language skills. These findings suggest the need for clear guidelines on how to use ChatGPT effectively.

This study tests whether sentence-level source text syntactic complexity predicts time-normalised disfluency in English–Korean simultaneous interpreting. Complexity is indexed by mean dependency distance (MDD); disfluency comprises silent pauses (≥1.0 s), filled pauses, repetitions, self-repairs, and other events, reported as rates (events·min⁻¹). Six graduate student interpreters produced sentence-aligned outputs, with sentence × interpreter as the observation unit. Analyses used a negative-binomial GLMM with a duration offset, complemented by Kruskal–Wallis tests across MDD tertiles. Results showed that higher MDD predicted higher total disfluency rates (IRR = 1.20, 95% CI [1.09, 1.32], p < .001), with only silent pauses and repetitions exhibiting reliable increases across complexity groups. These findings support treating disfluency as a rate-sensitive indicator of structural load rather than a categorical defect. Methodologically, the study demonstrates a tractable workflow for sentence-level alignment and incidence-rate modelling. Pedagogically, it motivates difficulty calibration by MDD and targeted practice to manage pausing and repetition in student interpreter training.

With the advancement of large language models, it has become increasingly critical to assess their capabilities and limitations to identify areas where human expertise remains essential. This study compares the performance of GPT-4 and 13 translation students in correcting accuracy errors in Korean-to-English financial texts to inform post-editing pedagogy in the era of generative AI. The analysis highlights GPT-4’s strong potential as a post-editing tool for domain-specific informational texts, demonstrating superior performance in correcting omissions, grammatical and terminological errors. However, its performance was inconsistent in addressing lexical ambiguity where students often outperformed it. In the case of syntactic errors, both GPT-4 and students well corrected errors that were easily identifiable, but neither group handled syntactic ambiguity effectively. These findings underscore the need to reconsider priorities in post-editing training and call for further investigations to better understand GPT’s strengths and limitations.

This study analyses Donald Trump’s inaugural addresses delivered in 2017 and 2025, focusing on how specific lexical and pragmatic choices construct political messaging. Combining corpus-based lexical analysis with discourse-pragmatic interpretation, it highlights the strategic use of language in constructing political identity. Key content words such as America, nation, and great emerge prominently in Trump’s speeches, reflecting recurring rhetorical patterns. It also examines pronouns like we, us, and our, analyzing their frequency and rhetorical function in constructing group identity. Using theories of presupposition and implicature, the study examines how key phrases such as “We will make America great again” and “The golden age of America begins right now” work beyond their literal meaning to reinforce national sentiment. Comparative analysis reveals a shift in rhetorical strategy: the 2017 speech relies more on emotional language, while the 2025 speech emphasizes institutional legitimacy. Together, these linguistic choices form a coherent rhetorical framework that influences political identity and affiliation. The findings suggest how political language can be strategically used to influence public perception, highlighting the importance of language choices made by influential political figures and the need for continued analysis of such discourse.

The present study investigates the semantic differences between the Korean adjective 불편하다 and the Japanese expression 不便だ, focusing on how learners can achieve more accurate translations. Although 불편하다 is often translated as 不便だ, their semantic ranges differ, especially regarding psychological discomfort, where mistranslations frequently occur. The study analyzed student writings from 2024 and conducted a 2025 instructional activity advising students to avoid using 不便だto assess its impact on translation accuracy. Results showed that overuse of 不便だwas common, and targeted instruction improved accuracy. However, learners still faced challenges expressing psychological discomfort in Japanese due to limited vocabulary. These findings highlight the importance of teaching lexical nuance and expanding vocabulary to enhance translation accuracy between Korean and Japanese.

The Gaomi dialect is a defining feature of Mo Yan’s fiction. As a subvariety of the Jiaoliao Mandarin group, it overlaps with but also diverges from Modern Standard Chinese, creating distinct challenges for translation. Dialect, as an essential element of source culture, faces the dual pressures of translatability and untranslatability. Red Sorghum Clan has been translated into Korean in four versions by three translators, each employing different strategies in rendering Gaomi dialect and conveying the original’s tone and meaning. The study finds a shared reliance on both literal translation and domestication, while individual translators show distinct approaches to addressing untranslatability, resulting in varied outcomes. This research underscores the decisive role of translation strategies in shaping the quality of dialect translation and provides insights for future practices in cultural and dialect translation of literary texts.