Cross-Situational statistical word learning:behaviors, mechanisms and constraints

描述（由申请人提供）：在自然主义的学习环境中，有无限多的可能的单词与世界配对。以前的研究，以解决这个映射问题集中在语言，社会和表征的限制在一个单一的时刻。拟议中的研究询问，不确定性问题是否也可以以另一种方式解决，不是在一次试验中，而是在多次试验中，不是在与一个词和潜在指称的一次遭遇中，而是在跨情境中。我们认为，一个跨情境的学习策略的基础上计算分布统计跨词，跨所指，最重要的是跨这两个共同出现的最终可以映射到正确的所指，尽管在个别的学习时刻的逻辑模糊。因此，拟议的研究重点是：（1）记录10至16个月大的婴儿的跨情境学习，（2）通过理论模拟和实验研究调查这种学习的基础机制，以及（3）研究统计学习如何积累。理解这些机制以及它们如何出错或得到支持，无疑是理解延迟或改变早期词汇学习的发展性语言障碍的根源的基础。实施有利于发育障碍儿童的程序通常涉及改变或突出学习环境的各个方面。这需要对统计学习的环境和过程的结构和可持续性有原则的理解。

DESCRIPTION (provided by applicant): There are an infinite number of possible word-to-world pairings in naturalistic learning environments. Previous studies to solve this mapping problem focus on linguistic, social, and representational constraints at a single moment. The proposed research asks if the indeterminacy problem may also be solved in another way, not in a single trial, but across trials, not in a single encounter with a word and potential referent but cross-situationally. We argue that a cross-situational learning strategy based on computing distributional statistics across words, across referents, and most importantly across the co-occurrences of these two can ultimately map individual words to the right referents despite the logical ambiguity in individual learning moments. Thus, the proposed research focuses on: (1) documenting cross-situational learning in infants from 10- to 16-months of age, (2) investigating the kinds of mechanisms that underlie this learning through both theoretical simulations and experimental studies, and (3) studying how statistical learning builds on itself accumulatively. Understanding those mechanisms and how they might go wrong or be bolstered are surely fundamental to understanding the origins of developmental language disorders that delay or alter early lexical learning. Implementing procedures to benefit children with developmental disorders typically involves altering or highlighting aspects of the learning environment. This requires a principled understanding of the structure and regularities of that environment and processes of statistical learning.