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

RI：小：阅读中眼动的计算分析：读者特征、认知状态和自然语言处理

• 批准号: 1815529
• 负责人: Roger Levy
• 金额: $ 40万
• 依托单位: Massachusetts Institute of Technology
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-01 至 2021-07-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1815529&HistoricalAwards=false
• 关键词: RI; Small; Computational; analysis; eye

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.

阅读是世界上最广泛实践的技能。它占据了我们日常生活的许多小时，对于在现代社会中成功运作至关重要。当我们阅读时，我们的眼睛以一种反映我们感知，处理和理解的方式的方式移动文本。该项目使用眼动追踪来开发一种新的方法来研究我们的眼睛在阅读过程中的移动以及眼睛运动模式可以揭示读者的语言知识及其与文本的互动。特别是，研究人员开发了基于眼动的方法，这些方法会自动确定读者的语言水平，他们对文本的理解程度以及他们发现的难度。通过考虑有关人类阅读方式的信息，该项目通过计算机进行自动文本处理。该研究计划通过推进我们对阅读过程中语言处理的科学理解并启用新技术，从而使社会受益匪浅，从而支持来自各种背景和技能水平的人类读者的新技术。它为未来的数字平台奠定了基础，使人们可以根据读者的需求和目标更容易访问文本信息，提高识字，学习新语言，并根据读者的需求和目标来个性化文本内容和复杂性。该项目通过在阅读自由文本的阅读过程中利用广泛的覆盖范围覆盖眼动模式来介绍一种新颖的概念和计算方法，以与本地和非本地人的扬声器一起研究人类阅读。它开发了一个计算框架，该框架将阅读时的眼睛运动与文本的语言特性，读者的语言知识及其在阅读过程中的认知状态联系起来。为了实现这一框架，该项目首先着重于使用眼动阅读以自动预测读者的语言水平并估算其对文本特定部分的理解。这些和其他相关的任务有助于表征语言理解方式如何随着时间的流逝表现出来，并导致开发用于本地和非本地阅读的预测计算框架。它的第二个重点是整合自然语言处理中的数据和表达方式，以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的法定任务，并被认为是值得通过基金会的知识分子优点和更广泛影响的审查标准来通过评估来支持的。

项目成果

Predicting Text Readability from Scrolling Interactions

通过滚动交互预测文本可读性

• 发表时间: 2021
• 期刊: Proceedings of the Conference on Natural Language Learning
• 作者: Gooding, Sian;Berzak, Yevgeni;Mak, Tony;Sharifi, Matt
• 通讯作者: Sharifi, Matt

Eye Movement Traces of Linguistic Knowledge

语言知识的眼动痕迹

• 发表时间: 2021
• 期刊: Proceedings of the Annual Conference of the Cognitive Science Society
• 作者: Berzak, Yevgeni;Levy, Roger P.
• 通讯作者: Levy, Roger P.

STARC: Structured Annotations for Reading Comprehension

• DOI: 10.18653/v1/2020.acl-main.507
• 发表时间: 2020-04
• 作者: Yevgeni Berzak;J. Malmaud;R. Levy

Bridging Information-Seeking Human Gaze and Machine Reading Comprehension

连接寻求信息的人类凝视和机器阅读理解

• 发表时间: 2020
• 期刊: Proceedings of the Conference on Natural Language Learning
• 作者: Malmaud, Jonathan;Levy, Roger P.;Berzak, Yevgeni
• 通讯作者: Berzak, Yevgeni