AI in Interpreting Training

Abstract

This paper presents a structured protocol for integrating artificial intelligence (AI) into interpreter training, with a focus on ChatGPT, speech-to-text, and text-to-speech tools. It outlines a step-by-step methodology developed through practical experience and student feedback, aiming to enhance autonomous practice and real-time, detailed feedback among interpreting students. The paper contextualizes the use of AI in interpreter training by discussing the theoretical foundations of AI technologies and the evolving role of generative AI in the interpreter training process. A pedagogical framework is proposed for classroom implementation, including prompt engineering, ChatGPT-generated speech, and AI-based performance evaluation. Students’ responses highlight key benefits such as flexibility, increased practice opportunities, and personalized feedback, while also acknowledging limitations related to emotional nuance and reliability. The study concludes with recommendations for the responsible use of AI and directions for future research on adaptive interpreter training.