Infants, children, and adults have been shown to track co-occurrence across ambiguous naming situations to infer the referents of new words. The extensive literature on this cross-situational word learning (CSWL) ability has produced support for two theoretical accounts—associative learning (AL) and hypothesis testing (HT)—but no comprehensive model of the behavior. We propose Word-Object Learning via Visual Exploration in Space (WOLVES), an implementation-level account of CSWL grounded in real-time psychological processes of memory and attention that explicitly models the dynamics of looking at a moment-to-moment scale and learning across trials. We use WOLVES to capture data from 12 studies of CSWL with adults and children, thereby providing a comprehensive account of data purported to support both AL and HT accounts. Direct model comparison shows that WOLVES performs well relative to two competitor models. In particular, WOLVES captures more data than the competitor models (132 vs. 69 data values) and fits the data better than the competitor models (e.g., lower percent error scores for 12 of 17 conditions). Moreover, WOLVES generalizes more accurately to three “held-out” experiments, although a model by Kachergis et al. (2012) fares better on another metric of generalization (Akaike Information Criterion [AIC]/Bayesian Information Criterion [BIC]). Critically, we offer the first developmental account of CSWL, providing insights into how memory processes change from infancy through adulthood. WOLVES shows that visual exploration and selective attention in CSWL are both dependent on and indicative of learning within a task-specific context. Furthermore, learning is driven by real-time synchrony of words and gaze and constrained by memory processes over multiple timescales. (PsycInfo Database Record (c) 2021 APA, all rights reserved)

中文翻译：

---

通过空间视觉探索进行单词-对象学习（WOLVES）：跨情境单词学习的神经过程模型。

婴儿、儿童和成人已被证明可以跟踪模糊命名情况下的共现，以推断新单词的所指对象。关于这种跨情境单词学习（CSWL）能力的大量文献支持了两种理论解释——联想学习（AL）和假设检验（HT）——但没有全面的行为模型。我们提出了通过空间视觉探索进行词-对象学习（WOLVES），这是一种基于记忆和注意力的实时心理过程的 CSWL 的实现级解释，它明确地模拟了观察即时尺度和学习的动态。跨越考验。我们使用 WOLVES 捕获了 12 项针对成人和儿童的 CSWL 研究的数据，从而提供了旨在支持 AL 和 HT 账户的全面数据账户。直接模型比较表明，WOLVES 相对于两个竞争对手模型表现良好。特别是，WOLVES 比竞争对手模型捕获更多数据（132 个数据值与 69 个数据值），并且比竞争对手模型更适合数据（例如，17 个条件中的 12 个条件的百分比错误分数较低）。此外，WOLVES 更准确地概括为三个“保留”实验，尽管 Kachergis 等人的模型。(2012) 在另一个泛化指标（Akaike 信息准则 [AIC]/贝叶斯信息准则 [BIC]）上表现更好。至关重要的是，我们提供 WOLVES 更准确地概括为三个“保留”实验，尽管 Kachergis 等人的模型。(2012) 在另一个泛化指标（Akaike 信息准则 [AIC]/贝叶斯信息准则 [BIC]）上表现更好。至关重要的是，我们提供 WOLVES 更准确地概括为三个“保留”实验，尽管 Kachergis 等人的模型。(2012) 在另一个泛化指标（Akaike 信息准则 [AIC]/贝叶斯信息准则 [BIC]）上表现更好。至关重要的是，我们提供CSWL 的第一个发展说明，提供了关于记忆过程如何从婴儿期到成年期变化的见解。WOLVES 表明，CSWL 中的视觉探索和选择性注意既依赖于特定任务环境中的学习，也表明学习的效果。此外，学习是由言语和目光的实时同步驱动的，并受到多个时间尺度上的记忆过程的约束。（PsycInfo 数据库记录 (c) 2021 APA，保留所有权利）