Reading is a process that unfolds across space and time, alternating between fixations where a reader focuses on a specific point in space, and saccades where a reader rapidly shifts their focus to a new point. An ansatz of psycholinguistics is that modeling a reader's fixations and saccades yields insight into their online sentence processing. However, standard approaches to such modeling rely on aggregated eye-tracking measurements and models that impose strong assumptions, ignoring much of the spatio-temporal dynamics that occur during reading. In this paper, we propose a more general probabilistic model of reading behavior, based on a marked spatio-temporal point process, that captures not only how long fixations last, but also where they land in space and when they take place in time. The saccades are modeled using a Hawkes process, which captures how each fixation excites the probability of a new fixation occurring near it in time and space. The duration time of fixation events is modeled as a function of fixation-specific predictors convolved across time, thus capturing spillover effects. Empirically, our Hawkes process model exhibits a better fit to human saccades than baselines. With respect to fixation durations, we observe that incorporating contextual surprisal as a predictor results in only a marginal improvement in the model's predictive accuracy. This finding suggests that surprisal theory struggles to explain fine-grained eye movements.

翻译：阅读是一个在空间和时间上展开的过程，交替进行着注视（读者将注意力聚焦于空间中的特定点）和扫视（读者将注意力快速转移到新的点）。心理语言学的一个基本假设是，对读者的注视和扫视进行建模能够揭示其在线句子处理的机制。然而，此类建模的标准方法依赖于聚合的眼动追踪测量以及施加了强假设的模型，忽略了阅读过程中发生的大部分时空动态。在本文中，我们提出了一种更通用的阅读行为概率模型，该模型基于一个标记时空点过程，不仅捕捉注视持续的时间，还捕捉其在空间中的落点位置以及发生的时间点。扫视使用霍克斯过程进行建模，该过程捕捉了每次注视如何激发在时间和空间上接近其位置的新注视发生的概率。注视事件的持续时间被建模为注视特定预测因子在时间上进行卷积的函数，从而捕捉溢出效应。实证结果表明，我们的霍克斯过程模型对人类扫视的拟合优于基线模型。关于注视持续时间，我们观察到将语境惊奇度作为预测因子纳入，仅能略微提升模型的预测准确性。这一发现表明，惊奇度理论难以解释细粒度的眼动行为。