EAPSI: Understanding attention during the early stages of language acquisition using a new tracking eye gaze method

在了解儿童如何学习第一个单词时，了解视觉注意力是如何被引导的尤为重要。从孩子的角度来看，学习的对象可以在许多方面有所不同。当接触到人类的语言时，孩子们可以选择凝视各种各样的物品，其中一些物品可能会提供信息，将单词（听觉信息）与他们看到的物理事物（视觉信息）联系起来。这个项目将应用尖端技术用于研究孩子们在学习时看的地方。本研究旨在为儿童眼动追踪研究中遇到的问题提供解决方案。日本京都大学的Nishida博士通过实施一种有前途的注视点估计技术，拥有帮助实现这一目标的知识和专业知识。目前观察学习过程中注意力集中情况的方法通常涉及在实验条件下使用眼睛注视跟踪。目前，存在多种硬件选项来完成此任务，但具有其自身独特的优点和缺点。移动的可穿戴式眼动追踪解决方案在较少限制的设置中提供更大的灵活性，但需要更长的设置时间、调整和校准。这增加了实验程序的整体侵入性，并经常导致儿童意识到这些设备。眼睛跟踪硬件未连接到孩子（例如，专用视频监视器）通常具有对注视方向的更精确的测量，但是缺乏在三维环境中测量注视的能力。该项目中使用的新方法将使用计算机视觉算法对超分辨率眼睛图像进行角膜反射分析，以更好地适应儿童行为任务。它有可能显着降低复杂性，在深度变化的条件下获得准确和精确的数据，以了解注意力在语言学习过程的早期阶段的作用。这个NSF EAPSI奖是与日本科学促进协会合作资助的。

When it comes to knowing how children learn their first words, understanding how visual attention is guided is especially important. Objects being learned can vary in many ways when taking a child's view of the world. When exposed to human speech, children have the option to gaze upon a wide range of items, some of which are potentially informative for grounding words (auditory information) to physical things they see (visual information). This project will apply cutting edge techniques used for study where children look when they learn. This research aims to develop a solution for the problems we encounter in child-directed eye tracking research. Dr. Nishida at Kyoto University, Japan, has the knowledge and expertise to help with achieving this goal by implementing a promising technique for point of gaze estimation.Current methods for observing how attention is focused during learning typically involve the use of eye gaze tracking under experimental conditions. Currently, multiple hardware options exist for accomplishing this task, but have their own unique set of advantages and disadvantages. Mobile, wearable eye tracking solutions provide more flexibility in less constrained settings but require longer setup times, adjustments, and calibration. This increases the overall intrusiveness of the experimental procedure and often leads to the child being aware of such devices. Eye-tracking hardware not attached to the child (e.g., a specialized video monitor) typically have more precise measurements of gaze orientation but lack the ability to measure gaze in three-dimensional environments. The new method that will be used in this project, analyzes corneal reflections using computer vision algorithms on super resolution eye images to better accommodate child behavioral tasks. It has the potential to significantly reduce the complexities involved in obtaining accurate and precise data under depth-varying conditions for understanding the role of attention during the early stages of the language learning process. This NSF EAPSI award is funded in collaboration with the Japan Society for the Promotion of Science.