Translation, Cognition & Behavior - Online First

Syntactic complexity poses significant challenges in simultaneous interpreting (SI), affecting both the process and product and requiring interpreters to cope using various tactics. The role of subject length in English-Arabic SI has received little attention. This study investigates the correlation between SL subject length and structural choices in Arabic SI. A bilingual corpus of authentic English conference speeches and their professional Arabic SIs was analyzed. The results revealed a tendency to mirror English subject–verb–object (SVO) structures by opting for the Arabic marked SVO pattern instead of the more typical verb–subject–object (VSO) order. Subject length was found to be a reliable predictor of structural choice, with a weak but statistically significant correlation indicating that longer subjects slightly increase the likelihood of selecting SVO. This pattern suggests that structural alignment is influenced by automatic priming tendencies interacting with strategic load management, with clear implications for interpreter training and professional practice.

Artificial intelligence (AI) has significantly improved the efficiency of translation and interpreting (T&I), yet its cognitive and psychological impacts remain underexplored. To address this, 299 Chinese translators and interpreters were surveyed, and interviews were conducted with 12 respondents, focusing on mental workload, anxiety, adaptation, and professional well-being. The results show that AI adoption reduces mental workload and improves professional well-being, but also increases the anxiety induced by AI use. However, this anxiety does not directly affect professional well-being. Effective adaptation strategies and continual training are essential for optimizing AI’s benefits. While AI streamlines initial T&I tasks, it increases cognitive demands during post-editing. These findings emphasize the need for a human-centered approach that balances AI’s efficiency gains with its negative cognitive effects, so as to foster a collaborative relationship between T&I professionals and AI.