EAGER: Pilot Investigation of Using Gaze in a Reading Tutor

EAGER：阅读导师使用凝视的试点调查

• 批准号: 1322174
• 负责人: David Mostow
• 金额: $ 30万
• 依托单位: Carnegie-Mellon University
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2013
• 资助国家: 美国
• 起止时间: 2013-03-01 至 2013-12-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1322174&HistoricalAwards=false
• 关键词: EAGER; Pilot; Investigation; Using; Gaze

The big question the PIs are addressing in this project is how to unobtrusively track silent reading of novice readers so as to be able to use an intelligent tutoring system to aid reading comprehension. This EAGER project focuses on the first steps in answering that question. This pilot project builds on previous work in vision and speech technology, sensor fusion, machine learning, user modeling, intelligent tutors, and eye movements in an effort to identify the feasibility of using eye tracking techniques, along with other information collected from an intelligent reading tutor, to predict reading difficulties of novice/young readers. In particular, the work plan includes collecting gaze data in real-world conditions in the context of using the existing Reading Tutor, designing software to display those traces so that accuracy can be guauged, testing gazepoint accuracy and detecting gaze-speech discrepancies, and using that data to develop heuristics for detecting tracking errors in real time and calibrating eye tracking data to noisy school environments, a primary environment where the augmented Reading Tutor would ultimately be used. The intellectual merit of this project is in identifying and addressing challenges in relating children's gaze data to their silent reading, in making technical contributions to calibrating eye trackers so that they can be used in normal everyday applications, and in setting the stage for intelligent tutors across diverse domains to exploit gaze more broadly.The project's most important potential broader impacts is in establishing a foundation for exploiting gaze input to build intelligent computing systems that can be used to help children with reading difficulties learn to read and read to learn. If successful, the PIs will develop a larger project that will extent the successful Project Listen Reading Tutor so that it can track readers as they are reading silently and help them with their comprehension -- both comprehension of text itself and strategies for coming to deep understanding.

在这个项目中，PI正在解决的一个大问题是如何不引人注目地跟踪新手读者的无声阅读，以便能够使用智能辅导系统来帮助阅读理解。这个急切的项目关注的是回答这个问题的第一步。这个试点项目建立在视觉和语音技术、传感器融合、机器学习、用户建模、智能导师和眼动方面的先前工作的基础上，努力确定使用眼睛跟踪技术以及从智能阅读导师收集的其他信息来预测新手/年轻读者阅读困难的可行性。特别是，工作计划包括在使用现有阅读辅导的情况下收集现实世界条件下的凝视数据，设计软件显示这些痕迹，以便可以猜测准确性，测试眼点精度和检测凝视-语音差异，并利用这些数据开发启发式方法，实时检测跟踪错误，并将眼睛跟踪数据校准到嘈杂的学校环境，这是最终将使用增强阅读辅导的主要环境。该项目的智力价值在于识别和解决将儿童的凝视数据与他们的无声阅读联系起来的挑战，为校准眼球追踪器做出技术贡献以便它们可以在正常的日常应用中使用，并为跨不同领域的智能教师更广泛地开发凝视奠定了平台。该项目最重要的潜在更广泛的影响是为利用凝视输入建立智能计算系统奠定基础，该系统可以用来帮助阅读困难的儿童学习阅读和阅读学习。如果成功，PIS将开发一个更大的项目，扩展成功的Project Listen阅读辅导，使其能够跟踪读者在默读时的情况，并帮助他们理解--包括对文本本身的理解和深入理解的策略。