In reading tasks drift can move fixations from one word to another or even another line, invalidating the eye tracking recording. Manual correction is time-consuming and subjective, while automated correction is fast yet limited in accuracy. In this paper we present Fix8 (Fixate), an open-source GUI tool that offers a novel semi-automated correction approach for eye tracking data in reading tasks. The proposed approach allows the user to collaborate with an algorithm to produce accurate corrections faster without sacrificing accuracy. Through a usability study (N=14) we assess the time benefits of the proposed technique, and measure the correction accuracy in comparison to manual correction. In addition, we assess subjective workload through NASA Task Load Index, and user opinions through Likert-scale questions. Our results show that on average the proposed technique was 44% faster than manual correction without any sacrifice in accuracy. In addition, users reported a preference for the proposed technique, lower workload, and higher perceived performance compared to manual correction. Fix8 is a valuable tool that offers useful features for generating synthetic eye tracking data, visualization, filters, data converters, and eye movement analysis in addition to the main contribution in data correction.

翻译：在阅读任务中，漂移可能导致注视点从一个单词移至另一个单词甚至另一行，从而使眼动追踪记录失效。手动校正耗时且具有主观性，而自动校正虽快速但准确性有限。本文提出Fix8（Fixate），一个开源的图形用户界面工具，为阅读任务中的眼动追踪数据提供了一种新颖的半自动化校正方法。该方法允许用户与算法协作，在不牺牲准确性的前提下更快地生成精确校正。通过一项可用性研究（N=14），我们评估了所提技术的时间效益，并与手动校正比较了校正准确性。此外，我们通过NASA任务负荷指数评估了主观工作负荷，并通过李克特量表问题收集了用户意见。结果表明，所提技术平均比手动校正快44%，且未损失任何准确性。此外，用户报告称相较于手动校正，他们更倾向于使用所提技术，工作负荷更低，且感知绩效更高。Fix8是一个有价值的工具，除了在数据校正方面的主要贡献外，还提供了生成合成眼动追踪数据、可视化、滤波器、数据转换器及眼动分析等实用功能。