從眼動解讀閱讀目標

Decoding Reading Goals from Eye Movements

October 28, 2024

作者: Omer Shubi, Cfir Avraham Hadar, Yevgeni Berzak

cs.AI

摘要

讀者對其閱讀的文本可能有不同的目標。這些目標是否可以從他們在文本上的眼動模式中解讀出來？在這項研究中，我們首次檢驗了是否可能解碼在日常生活中常見的兩種閱讀目標：尋求資訊和普通閱讀。利用大規模眼動追蹤數據，我們應用了眼動和文本的眾多最先進模型，涵蓋不同的架構和數據表示策略，並進一步引入了一個新的模型集成。我們系統地評估這些模型在三個泛化級別上：新的文本項目、新的參與者以及兩者的組合。我們發現眼動包含了對這一任務非常有價值的信號。我們進一步進行了一項錯誤分析，該分析基於先前對普通閱讀和尋求資訊之間差異的實證研究，並利用豐富的文本標註。這一分析揭示了文本項目和參與者眼動的關鍵特性，這些特性有助於解決這一任務的困難。

English

Readers can have different goals with respect to the text they are reading. Can these goals be decoded from the pattern of their eye movements over the text? In this work, we examine for the first time whether it is possible to decode two types of reading goals that are common in daily life: information seeking and ordinary reading. Using large scale eye-tracking data, we apply to this task a wide range of state-of-the-art models for eye movements and text that cover different architectural and data representation strategies, and further introduce a new model ensemble. We systematically evaluate these models at three levels of generalization: new textual item, new participant, and the combination of both. We find that eye movements contain highly valuable signals for this task. We further perform an error analysis which builds on prior empirical findings on differences between ordinary reading and information seeking and leverages rich textual annotations. This analysis reveals key properties of textual items and participant eye movements that contribute to the difficulty of the task.