Monolingual versus bilingual captioning: An ergonomic perspective on computer-assisted simultaneous interpreting

As generative AI and machine learning reshape industries, interpreters are required to navigate a dynamic ecosystem where interpreting skills and digital solutions converge. While extensive research has explored the effects of technologies on the interpreting process and output quality, the ergonomic needs of interpreting learners interacting with different technologies have received less scholarly attention. This is particularly evident in training on computer-assisted simultaneous interpreting (CASI), where the successful interaction between human interpreters and technology is crucial for enhancing student interpreters’ learning outcomes and training effectiveness. This study examines the impact of two live captioning systems on student interpreters’ performance during English-to-Chinese simultaneous interpreting (SI) tasks: YouTube’s monolingual Automatic Speech Recognition (ASR) captions and iFLYTEK’s bilingual machine interpreting outputs. Twenty second-year postgraduate students participated in the experiment under these two CASI conditions. Accuracy, fluency, target language quality, and overall performance of the participants’ interpreting outputs were assessed. In the present study, the introduction of live captioning significantly reduced student interpreters’ performance. Furthermore, students working with monolingual captioning demonstrated better performance across all quality dimensions relative to those utilising bilingual captioning. This study highlights the critical role of ergonomics in the CASI tool and the need for comprehensive interpreter training.