Human–machine interaction in simultaneous interpreting workflow: The effect of ASR-generated live captions on student interpreting of speeches at different rates

This study investigates human–machine interaction in the workflow of automatic speech recognition (ASR)-assisted simultaneous interpreting of speeches with different delivery rates. Specifically, the study examines how student interpreters interact with ASR-generated text and how it differentially affects interpreting performance across speech rates. To address these questions, caption-viewing patterns (with ASR live captions) and interpreting performance at varying speech rates were collected and analysed. The findings indicate that interpreting performance improves significantly as input rates increase when supported by ASR-generated text, whereas no notable improvement is observed at slower speech rate. Patterns and behaviour of how student interpreters resort to live captions were found to be subject to individual differences. The study highlights the need for targeted training to help student interpreters utilise live transcriptions to facilitate their performance.