Computer-Assisted Consecutive Interpreting and Its Impact on Student Interpreters: An Empirical Study Using iFLYTEK Hearing

Abstract

With the rapid advancement of artificial intelligence technology, the application of Computer-Assisted Interpretation (CAI) in the field of Consecutive Interpretation (CI) has become increasingly prevalent. Existing research predominantly focuses on the synergistic effects of AI tools and professional interpreters in Simultaneous Interpretation (SI) scenarios, while the efficacy of CAI for student interpreters in CI tasks remains underexplored. This study employs empirical analysis to address two core questions: (1) What impact does CAI have on the interpreting quality of student interpreters in CI? (2) What underlying factors mediate this impact?

Adopting a controlled experimental design, the study recruited 11 third- and fourth-year English majors (all with less than 12 months of interpreting training) as participants. Each participant performed two interpreting tasks of comparable theme, length, and difficulty, with the variable being "use or non-use of CAI tools." Quantitative and qualitative analyses were conducted using iFlytek Hearing for real-time transcription and ERNIE Bot for quality evaluation assistance. Questionnaires and semi-structured interviews were utilized to measure and collect participants’ experiential feedback. Data were analyzed using SPSS software, yielding the following conclusions: Findings suggest that while CAI did not significantly improve overall interpreting quality, it partially supported memory and accuracy. However, cognitive overload and interpreter anxiety limited its effectiveness. These results provide empirical evidence for refining CAI integration in interpreter training. However, this experiment, with no training exposure and a rather small sample size, is more of an exploratory study.