Researchers from the Faculty of Data and Decision Sciences at the Technion have developed a technology capable of identifying various aspects of a reader’s interaction with a text that is based solely on their eye movements.
The team’s findings were presented at Association for Computational Linguistics, a conference in the field of Natural Language Processing (NLP) in Vienna. The research was led by doctoral student Omer Shubi, together with master’s student Cfir Hadar, under the supervision of Dr. Yevgeni Berzak.
People read texts with different goals. Whether it’s a novel, a cooking recipe, a newspaper article, or a scientific paper, each type of text can be approached with various intentions. Two common reading goals are general comprehension (regular reading) and information search.
The researchers developed computational models that combine eye-tracking with text processing. These models can accurately detect a reader’s purpose with approximately 90% accuracy, and nearly 80% accuracy within just two seconds from the moment the reading started.
According to Dr. Berzak, “This study is part of a broader research program in which we are developing AI models that infer, in real time and from eye movements alone, key aspects of the reader’s linguistic knowledge, their interaction with the text, the difference between a first and a second reading, the readability of a given text, and even the specific information the reader is seeking.
“These studies pave the way for new methods in assessing linguistic knowledge, personalizing texts according to the reader’s linguistic and reading proficiency, improving accessibility to textual information for various populations, and more.”
Eye-tracking technologies are becoming increasingly widespread, affordable, and accurate, with some now available on common devices like iPads and smartphones. The researchers hope these developments will accelerate the adoption of their models, benefiting both users and content providers in fields such as education, government, and media.
Dr. Yevgeni Berzak, a faculty member in the Faculty of Data and Decision Sciences and head…
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