Grounded in the pedagogical goals of interpreting training, this study explores the impact of automatic speech recognition technology on cognitive processing in simultaneous interpreting, specifically, how trainee interpreters handle Chinese head-final noun phrases with varying dependency distances, i.e., how they navigate syntactic asymmetry between Chinese and English and capture information focus in simultaneous interpreting with synchronous captioning, with particular emphasis on the effects of highlighting head nouns and dependency distance variations. To examine these factors, an eye-tracking experiment involving 30 Chinese trainee interpreters was conducted, where participants interpreted a speech which contained 16 experimental sentences with controlled dependency distances in noun phrases featuring head nouns highlighted within the captions, in comparison with 16 control sentences without highlighted head nouns. Eye movements in the interpreting process and interpreting performances were analysed. The results indicate that head noun highlighting enhances cognitive processing and information completeness during simultaneous interpreting by facilitating deeper reprocessing and comprehension, particularly for sentences with longer dependency distances. The study reveals that highlighting head nouns lowers omission rates and encourages more structured interpreting output, like prepositional phrases or relative clauses, depending on the dependency distance. Without highlighting, interpreting output tends to be more flexible but less accurate due to incomplete information rendering. These findings underscore the potential of incorporating visual aids, such as head noun highlighting, into interpreter training programs to enhance accuracy and cognitive resource management.
CORE (COnnecting REpositories)
CORE (COnnecting REpositories)