Translation and Interpreting Research

Museums are crucial cultural and educational institutions that facilitate visitors’ learning by integrating diverse modes of engagement, including linguistic, visual, auditory, and spatial elements. Consequently, coherence of these elements is crucial for effectively presenting information and maximizing its impact on visitors. Utilizing Kress and van Leeuwen’s (2020) principles of composition, specifically focusing on information value and salience, this study sought to assess text-image interaction in the images at the Omidvar Brothers Museum and their corresponding Persian labels, as well as to compare the interaction in the Persian labels with that in the English labels. The analysis revealed that the criterion “information value: left vs. right” received minimal attention, while the “information value: center vs. margins” criterion was the most consistently met in both Persian and English descriptions. However, the overall accuracy of multimodal interaction between the images and labels decreased by 7.40% in the English labels compared to the Persian labels, indicating a decline in translator performance relative to the original authors. This reduction in verbal-visual coherence suggests a less engaging experience for English-speaking foreign visitors compared to Iranian audiences. These results emphasize the necessity of addressing multimodality within museum contexts, as such focus can significantly enhance visitor experiences and deepen their understanding of museum exhibits.

The ecological turn in translation studies subverts anthropocentric perspectives and redefines translation as a multispecies, semiotic process that transcends human language. Eco-translation, a central concept within this turn, extends the field of translation to include non-human actors and ecological networks, allowing for a more inclusive description of meaning-making. Yet this turn has also brought academics a sense of disorientation and solastalgia as scholars have to grapple with the tension between preserving traditional disciplinary boundaries and embracing the expansive horizons of transdisciplinary approaches. The current article traces the ecological turn using Doris Bachmann-Medick’s three-stage model of disciplinary turn: thematic expansion, metaphorical application, and methodological refinement. It maps the evolution of eco-translation from narrowly defined practices focused on ecological themes to a broader, inclusive framework that challenges the field’s traditional foundations. The article also examines the emotional and intellectual consequences of this turn, particularly the solastalgic experience of scholars experiencing the loss of familiar disciplinary contours while adapting to new paradigms.

This empirical investigation examines the repair strategies used by trainee interpreters in English-Persian simultaneous (SI) and consecutive interpreting (CI) modes. The research seeks to investigate two main questions: whether there are differences in the frequency of repairs between SI and CI, and whether there are variations in the sorts of repair strategies employed in both modes. The study involved nine trainees from Shahid Bahonar University of Kerman who were learning interpreting. The study employed a 4-minute speech from Voice of America English News, which discussed the influence of vitamins on preventing the advancement of AIDS in women. Occurrences of self-repairs were detected using Tang’s (2020c) framework. The findings revealed a notable disparity in the frequency of repair strategies between CI and SI modes, with CI trainees utilizing a greater number of repairs. In addition, the trainees in the CI mode achieved superior scores in explicitation and synonym techniques. The results emphasize the unique patterns of repair strategies in both consecutive and simultaneous interpretation, reflecting the importance of focused training to improve interpreters’ abilities in both modes. Interpreter training programs may consider including explicit instruction on repair procedures and placing emphasis on evaluating their use in performance assessments.

AI-assisted translation has gained increasing attention in recent years, yet its effectiveness remains underexplored. The present study sought to shed light on the role of AI (ChatGPT) in mediating translation. To this end, 46 postgraduate ESP students majoring in three sub-disciplines of politics (across three classes) were selected through convenience sampling. No outliers were identified in these classes, and each was assigned to one experimental group (AI-assisted group, N = 16; AI–Human Revised group, N = 16; Human-only Scaffolded group, N = 14). A posttest-only control group design was adopted, and each group was mediated according to its respective intervention protocol. AI was instructed to follow a graduated mediation protocol developed for the purposes of this study. The final translations were evaluated both qualitatively and quantitatively. Findings revealed that the end product of the AI-assisted group, compared with the human-involved groups, exhibited major translation deficiencies ranging from the lexico-semantic level to syntax, the syntax–semantic interface, and rhetorical patterns. Additional procedural deficiencies were also observed and reported. Furthermore, participants’ translations were assessed using a rubric, and quantitative analysis showed that both human-involved groups significantly outperformed the AI-only group.

This study evaluates the translation quality of two open letters by Iran’s Supreme Leader, addressed to Western youth, using House’s TQA model (2015). The research identifies both the strengths and limitations of the model in assessing texts of this nature. Through a detailed qualitative, comparative, and descriptive analysis, the study highlighted House’s model as a tool for analyzing field, tenor, and mode but also noted significant gaps, including the lack of differentiation between local and global cultural filters, the absence of non-dimensional mismatches, and the failure to provide practical solutions for identified issues. The findings suggested expanding House’s model to incorporate a broader classification of cultural filters and address non-dimensional mismatches. This study underscored the need to adapt quality assessment approaches to specific text types and linguistic functions. The insights offered not only contributed to theoretical advancements but also provided practical guidelines for improving translation quality assessment endeavors in any type of discourse.

This study examines the accessibility of translated navigational signs in Tehran Metro as a key site of public translation. Using field observations supported by the User-Centered Translation (UCT) framework, it assesses the clarity, consistency, and usability of bilingual signage and other multimedia  features across multiple metro stations and lines. The analysis identifies recurring inconsistencies in transliteration, translation choices, and the alignment between station names at stations and on the official metro map. These variations demonstrate the lack of a standardized approach to multilingual communication within the network and highlight the impact of such discrepancies on user navigation. The study contributes empirical data to ongoing discussions of translation in public spaces by showing how multilingual signage practices can either facilitate or hinder effective wayfinding in transit environments.