Statistical Learning in Infant Language Acquisition

项目摘要/摘要 第一语言习得是典型的人类发展的标志。大量的研究表明 婴儿在语言输入中发现统计规律的能力有助于语言学习。然而， 这一文献的影响一直受到限制，因为它未能将统计学习与新兴的 研究和理论主要集中在婴儿的实时语言处理上。当前的应用程序是有动机的 通过统计规则促进婴儿有效地编码和处理语言的前提 输入。为此，婴儿会对可能的下游输入进行预测。这些预测通常是 不正确的渲染预测错误--这可能是后续学习的潜在数据来源。输入即为 概率和/或先前导致预测误差的数据提供了丰富的信息，指导婴儿的 随之而来的关注和学习。我们假设统计规律性是 影响这一过程的信息，以及语言学和 非语言环境。到目前为止，还没有先前的研究操纵过婴儿时期的统计规律。 语言处理任务；研究是必要的，以判断之间可能的关系 发展过程中输入和实时语言行为的统计规律。在建议的 实验中，我们将测量婴儿在预测语言过程中使用顺序统计规则的情况 处理任务(目标1)，评估统计规则对基于预测误差的学习的影响(目标2)， 并考察了由于统计结构和预测误差引起的不确定性在激发婴儿积极性方面的作用 语言学习中的探索性行为(目标3)。拟议的研究结果将促进 通过扩大我们对统计之间的关系的理解，获得积极的发展成果 语言输入的结构和在语言发展过程中展开的实时过程。就像我们的 以前的统计学习研究，这些对典型发育婴儿的研究结果将 推动未来的调查，包括有非典型语言发育风险的婴幼儿 轨迹。

Project Summary/Abstract First language acquisition is a hallmark of typical human development. A substantial body of research suggests that infants’ ability to detect statistical regularities in language input facilitates language learning. However, the impact of this literature has been limited by its failure to connect statistical learning with the burgeoning body of research and theories focused on infants’ real-time language processing. The current application is motivated by the premise that statistical regularities facilitate infants’ attempts to efficiently encode and process language input. To this end, infants generate predictions about likely downstream input. These predictions are often incorrect, rendering prediction errors – a potentially potent source of data for subsequent learning. Input that is probabilistic and/or that has previously led to prediction errors provides information-rich data, guiding infants’ subsequent attention and learning. We hypothesize that statistical regularities are an important source of information influencing this process, along with the other contextual cues available in both the linguistic and nonlinguistic environment. To date, no prior studies have manipulated statistical regularities during infant language processing tasks; research is necessary to adjudicate amongst the possible relationships between statistical regularities in the input and real-time language behaviors during development. In the proposed experiments, we will measure infants’ use of sequential statistical regularities during predictive language processing tasks (Aim 1), assess the impact of statistical regularities on prediction error-based learning (Aim 2), and examine the role of uncertainty due to statistical structure and prediction error in motivating infants’ active exploratory behavior during language learning (Aim 3). The results of the proposed research will promote positive developmental outcomes by expanding our understanding of the relationship between the statistical structure of language input and real-time processes that are unfolding during language development. As in our previous statistical learning research, the outcomes of these studies with typically-developing infants will motivate future investigations that include infants and young children at risk for atypical language development trajectories.