An Eye-Tracking Study on the Use of Machine Translation Post-Editing and Automatic Speech Recognition in Translations for the Medical Domain (2024)

Abstract: This EAMT-funded eye-tracking study investigates the impact of Machine Translation Post-Editing and Automatic Speech Recognition on English-Romanian translations of patient-facing medical texts. This paper provides an overview of the study objectives, setup and preliminary results.

## project overview research in the medical domain indicates that medical texts for patients, such as patient information leaflets (pils) and informed consent forms (icfs), are too complex to be understood by their lay target audience, due to linguistic features such as medical jargon or syntactic complexity @xcite . in some cases, medical translators can replicate and/or exacerbate these comprehensibility issues through their translation choices @xcite . given the technologisation seen across the broader translation industry @xcite , it is worth considering whether and how could existing technologies be leveraged to support medical translators in producing more readable and lay-friendly translations of medical texts for patients. the present study aims to address this research gap by investigating the impact of machine translation post-editing (mtpe), dictated translation using an automatic speech recognition (asr) tool and standard typed translation in the context of icf translations from english into romanian (en-ro). the study draws on prior research on translation modalities @xcite and measures this impact © 2024 the authors. this article is licensed under a creative commons 4.0 licence, no derivative works, attribution, cc-by-nd. across four variables: (1) output quality, readability and lay-friendliness; (2) cognitive load, measured using an eye-tracker; (3) task productivity; and (4) participants' self-reported perceptions. the main objective of this study is to assess whether mtpe, dictated translation using asr or typed translation has a significant effect on participating translators' product and process and would thus lend itself better to patient-facing medical translation workflows. more specifically, we are interested in finding out which condition produces the most readable and lay-friendly translation, and how it impacts translators' speed, cognitive load and preferences compared to the other conditions. these results will help inform guidelines and training materials on mtpe and asr for medical translators working on patient-facing medical texts. ## study design and methodology data collection took place in march 2023 in cluj-napoca, romania, and forms part of a three-year doctoral project (2022-2025) at the university of vienna centre for translation studies. seven participants, all professional medical translators, performed three en-ro translation tasks using the computer-assisted translation (cat) tool matecat: foot_0 (1) typed translation from scratch, still the dominant way to translate @xcite ; during the tasks, participants' eye movements were recorded using an eyelink portable duo eye tracker, foot_3 with their on-screen behaviour and keystrokes recorded in the weblink software. 5 participants also filled out pre-and post-task questionnaires on their mtpe and asr experience and in-task performance. they were compensated for their participation, which took up to 3 hours. ## analysis and future work the study data (eye-tracking video recordings, keystroke-and time-logging, questionnaires, and target translations) are currently undergoing statistical analysis (including regression modeling). preliminary results suggest: these results suggest that mtpe and asr do not hinder the translation process from a cognitive standpoint, are faster than typed translation, and there is openness to their adoption among our study participants, though this is more limited for mtpe. in future work, we will measure the effect of mtpe, asr and typed translation on out-