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Prediction of recall accuracy in a contextual understanding task using eye movement features

机译:使用眼球运动特征在上下文理解任务中预测召回准确性

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Contextual understanding, which consists of memory, reasoning and recall, is a key process of human-computer interactions and interfaces. To determine the possibility of predicting the recall accuracy of reading and memorizing tasks using features of eye movements for a targeted text, a contextual understanding task experiment was conducted. The relationship between eye movement during memorization and recall performance was hypothesized. Viewer's eye-movements during the reading of definition statements were observed, and twelve sector features of these eye-movements across a two-dimensional space were measured. The prediction procedure was developed using Support Vector Regressions with Gaussian kernel. The correlational relationship between predicted and experimental recall accuracies was significant; therefore the hypothesis was supported. Also, it was found that prediction performance depended on a combination of features of eye movements.
机译:语境理解包括内存,推理和召回,是人机交互和接口的关键过程。 为了确定使用针对目标文本的眼球运动的特征来预测读取和记忆任务的召回准确性的可能性,进行了上下文理解任务实验。 记忆中的眼球与召回性能之间的关系是假设的。 观察观察者在读取定义陈述期间的观看者的微动,测量了两维空间上的这些眼睛运动的12个扇区特征。 使用与高斯内核的支持向量回归开发了预测程序。 预测和实验召回精度之间的相关关系是显着的; 因此,支持假设。 而且,发现预测性能依赖于眼球运动的特征的组合。

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