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- W4387323611 abstract "Language learners should regularly engage in reading challenging materials as part of their study routine. Nevertheless, constantly referring to dictionaries is time-consuming and distracting. This paper presents a novel gaze-driven sentence simplification system designed to enhance reading comprehension while maintaining their focus on the content. Our system incorporates machine learning models tailored to individual learners, combining eye gaze features and linguistic features to assess sentence comprehension. When the system identifies comprehension difficulties, it provides simplified versions by replacing complex vocabulary and grammar with simpler alternatives via GPT-3.5. We conducted an experiment with 19 English learners, collecting data on their eye movements while reading English text. The results demonstrated that our system is capable of accurately estimating sentence-level comprehension. Additionally, we found that GPT-3.5 simplification improved readability in terms of traditional readability metrics and individual word difficulty, paraphrasing across different linguistic levels." @default.
- W4387323611 created "2023-10-04" @default.
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- W4387323611 date "2023-10-09" @default.
- W4387323611 modified "2023-10-10" @default.
- W4387323611 title "Gaze-Driven Sentence Simplification for Language Learners: Enhancing Comprehension and Readability" @default.
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- W4387323611 doi "https://doi.org/10.1145/3610661.3616177" @default.
- W4387323611 hasPublicationYear "2023" @default.
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