Adaptive Real-Time Translation Assistance Through Eye-Tracking

This study introduces the Eye-tracking Translation Software (ETS), a system that leverages eye-tracking data and real-time translation to enhance reading flow for non-native language users in complex, technical texts. By measuring the fixation duration, we can detect moments of cognitive load, ETS s...

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Main Authors: Dimosthenis Minas, Eleanna Theodosiou, Konstantinos Roumpas, Michalis Xenos
Format: Article
Language:English
Published: MDPI AG 2025-01-01
Series:AI
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Online Access:https://www.mdpi.com/2673-2688/6/1/5
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author Dimosthenis Minas
Eleanna Theodosiou
Konstantinos Roumpas
Michalis Xenos
author_facet Dimosthenis Minas
Eleanna Theodosiou
Konstantinos Roumpas
Michalis Xenos
author_sort Dimosthenis Minas
collection DOAJ
description This study introduces the Eye-tracking Translation Software (ETS), a system that leverages eye-tracking data and real-time translation to enhance reading flow for non-native language users in complex, technical texts. By measuring the fixation duration, we can detect moments of cognitive load, ETS selectively provides translations, maintaining reading flow and engagement without undermining language learning. The key technological components include a desktop eye-tracker integrated with a custom Python-based application. Through a user-centered design, ETS dynamically adapts to individual reading needs, reducing cognitive strain by offering word-level translations when needed. A study involving 53 participants assessed ETS’s impact on reading speed, fixation duration, and user experience, with findings indicating improved comprehension and reading efficiency. Results demonstrated that gaze-based adaptations significantly improved their reading experience and reduced cognitive load. Participants positively rated ETS’s usability and were noted through preferences for customization, such as pop-up placement and sentence-level translations. Future work will integrate AI-driven adaptations, allowing the system to adjust based on user proficiency and reading behavior. The study contributes to the growing evidence of eye-tracking’s potential in educational and professional applications, offering a flexible, personalized approach to reading assistance that balances language exposure with real-time support.
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issn 2673-2688
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spelling doaj-art-6a5dd39355cc423281058ef28743241f2025-01-24T13:17:22ZengMDPI AGAI2673-26882025-01-0161510.3390/ai6010005Adaptive Real-Time Translation Assistance Through Eye-TrackingDimosthenis Minas0Eleanna Theodosiou1Konstantinos Roumpas2Michalis Xenos3Software Quality and Human-Computer Interaction Laboratory, University of Patras, 26504 Rio, GreeceSoftware Quality and Human-Computer Interaction Laboratory, University of Patras, 26504 Rio, GreeceSoftware Quality and Human-Computer Interaction Laboratory, University of Patras, 26504 Rio, GreeceSoftware Quality and Human-Computer Interaction Laboratory, University of Patras, 26504 Rio, GreeceThis study introduces the Eye-tracking Translation Software (ETS), a system that leverages eye-tracking data and real-time translation to enhance reading flow for non-native language users in complex, technical texts. By measuring the fixation duration, we can detect moments of cognitive load, ETS selectively provides translations, maintaining reading flow and engagement without undermining language learning. The key technological components include a desktop eye-tracker integrated with a custom Python-based application. Through a user-centered design, ETS dynamically adapts to individual reading needs, reducing cognitive strain by offering word-level translations when needed. A study involving 53 participants assessed ETS’s impact on reading speed, fixation duration, and user experience, with findings indicating improved comprehension and reading efficiency. Results demonstrated that gaze-based adaptations significantly improved their reading experience and reduced cognitive load. Participants positively rated ETS’s usability and were noted through preferences for customization, such as pop-up placement and sentence-level translations. Future work will integrate AI-driven adaptations, allowing the system to adjust based on user proficiency and reading behavior. The study contributes to the growing evidence of eye-tracking’s potential in educational and professional applications, offering a flexible, personalized approach to reading assistance that balances language exposure with real-time support.https://www.mdpi.com/2673-2688/6/1/5eye-tracking technologyreal-time translationreading comprehensionhuman-computer interactionadaptive learning toolsnon-native language assistance
spellingShingle Dimosthenis Minas
Eleanna Theodosiou
Konstantinos Roumpas
Michalis Xenos
Adaptive Real-Time Translation Assistance Through Eye-Tracking
AI
eye-tracking technology
real-time translation
reading comprehension
human-computer interaction
adaptive learning tools
non-native language assistance
title Adaptive Real-Time Translation Assistance Through Eye-Tracking
title_full Adaptive Real-Time Translation Assistance Through Eye-Tracking
title_fullStr Adaptive Real-Time Translation Assistance Through Eye-Tracking
title_full_unstemmed Adaptive Real-Time Translation Assistance Through Eye-Tracking
title_short Adaptive Real-Time Translation Assistance Through Eye-Tracking
title_sort adaptive real time translation assistance through eye tracking
topic eye-tracking technology
real-time translation
reading comprehension
human-computer interaction
adaptive learning tools
non-native language assistance
url https://www.mdpi.com/2673-2688/6/1/5
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AT eleannatheodosiou adaptiverealtimetranslationassistancethrougheyetracking
AT konstantinosroumpas adaptiverealtimetranslationassistancethrougheyetracking
AT michalisxenos adaptiverealtimetranslationassistancethrougheyetracking