RI: Small: Computational analysis of eye movements in reading: reader characteristics, cognitive state, and natural language processing

阅读是世界上应用最广泛的技能。它占据了我们日常生活的许多小时，对于现代社会的成功运作至关重要。当我们阅读时，我们的眼睛以一种反映我们如何感知、处理和理解文本的方式移动到文本上。这个项目使用眼球跟踪来开发一种新的方法来研究我们的眼睛在阅读过程中是如何移动的，以及眼球运动模式可以揭示读者的语言知识以及他们如何与文本互动。特别是，研究人员开发了基于眼球跟踪的方法，自动确定读者的语言熟练程度、他们对文本的理解程度以及他们觉得它有多难。该项目通过考虑有关人类阅读方式的信息，改进了机器的自动文本处理。这项研究计划通过促进我们对阅读过程中语言处理的科学理解，并使新技术能够支持来自广泛背景和技能水平的人类读者，从而使社会受益。它为未来的数字平台奠定了基础，使人们更容易获取文本信息，提高识字能力，学习新的语言，并根据读者的需求和目标个性化文本内容和复杂性。该项目引入了一种新的概念和计算方法，通过利用自由形式文本阅读过程中广泛覆盖的眼动模式，研究母语和非母语人士的人类阅读。它开发了一个计算框架，将阅读中的眼动与文本的语言属性、读者的语言知识和他们在阅读过程中的认知状态联系起来。为了实现这一框架，该项目首先专注于利用阅读中的眼动来自动预测读者的语言水平，并估计他们对文本特定部分的理解。这些任务和其他相关任务有助于表征语言理解是如何在凝视中表现出来的，并随着时间的推移而展开，也导致了针对母语和非母语阅读的预测性计算框架的发展。它的第二个重点是在自然语言处理中整合眼睛跟踪的数据和表示，目的是开发支持和增强人类阅读和语言学习的应用程序。该奖项反映了NSF的法定使命，并通过使用基金会的智力优势和更广泛的影响审查标准进行评估，被认为值得支持。

Reading is the most widely practiced skill in the world. It occupies many hours of our daily lives and is crucial to functioning successfully in modern society. When we read, our eyes move over the text in a way that reflects how we perceive, process, and understand it. This project uses eye tracking to develop a new approach to studying how our eyes move during reading and what eye movement patterns can reveal about readers' linguistic knowledge and how they interact with text. In particular, the researchers develop eye tracking-based methods that automatically determine readers linguistic proficiency, how well they understand the text, and how difficult they find it. The project improves automatic text processing by machines, by taking into account information about how humans read. This research program benefits society by advancing our scientific understanding of language processing during reading and enabling new technologies that support human readers from a wide range of backgrounds and skill levels. It lays the foundations for future digital platforms that make it easier for people to access textual information, improve literacy, learn new languages, and personalize text content and complexity according to readers' needs and goals.The project introduces a novel conceptual and computational approach to studying human reading with both native and non-native speakers, by leveraging broad coverage eye movement patterns during reading of free-form text. It develops a computational framework that connects eye movement in reading to linguistic properties of the text, the readers' linguistic knowledge and their cognitive state during reading. To realize this framework, the project first focuses on using eye movement in reading to automatically predict readers' linguistic proficiency and estimate their comprehension of specific parts of a text. These and other related tasks help to characterize how language comprehension manifests in gaze and unfolds over time, and also lead to the development of a predictive computational framework for native and non-native reading. Its second focus is on integrating data and representations from eye tracking in natural language processing, with the aim of developing applications which support and enhance human reading and language learning.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.