A Study on AI-assisted and Skill-based Class Training Designed for English-Chinese Consecutive Interpretation

This paper probes into the essential role of AI in interpretation class training based on a half-a-year teaching empirical experiment, which focuses its implications on the design of the training materials and interpreting production evaluation. AI can produce a wide range of texts tailored for certain topics with varied difficulties and linguistic styles, greatly decreasing the effort of interpreting trainers’ and generate varied training drills that meet a variety of interpreting trainees’ needs. Besides, AI-generated audio clips can imitate diversified accents and intonations at different speeds, bringing forth practical audio drills to promote students' flexibility, comprehension capacities, and note-jotting in English-Chinese consecutive interpretation (ECCI for short). The great capacity of AI translation has been providing instantaneous and good enough translations for interpreting trainees to compare and assess their interpreting production, aiding them in terms of the greater flexibility in language shift, proficiency and fluency of the information conveyance, and in developing effective and proficient interpretation skills in trainees' training of interpretation. AI's greatness in generating training contents and translations can significantly boost the proficiency of interpretation skill acquisition and teaching, ushering in tailored and varied drills which enable the sustainable development of trainees' interpretation competence.