Infant statistical learning: Resilience, longevity, and specificity

 描述(由申请者提供)：尽管存在许多感知和认知方面的挑战，但发育中的婴儿通常以惊人的速度获得语言。婴儿可能会通过跟踪环境中的规律来开始学习语言。具体地说，研究表明，婴儿拥有强大的计算机制，可以支持从流利的语音中分割单词，并促进单词学习。问题是，很少有研究 关于统计规则在多大程度上支持幼儿经常面临的具有挑战性的学习条件下的早期语言习得。这项研究的目的是通过评估统计学习如何支持(1)背景噪声中的语音分割和单词学习，(2)婴儿在长期记忆中编码词汇表征的能力，以及(3)婴儿以适当的水平和细节类型表征新分割的单词的能力，来促进婴儿语言习得的综合和全面的理论。三个目标将通过九个实验来解决，这些实验旨在测试在自然语言输入中发现的统计规律如何支持发展框架内的韧性、寿命和表征专一性。婴儿将熟悉一个简短的自然意大利语语料库，然后测试他们辨别内部同现模式强与弱的单词的能力(8个月和11个月大的婴儿)，或者将这些单词与新事物(17个月大的婴儿)联系起来的能力。实验旨在测试婴儿如何应对同时的学习挑战。我们将测试以下预测：强音节共现模式将支持(1)在噪音中的语音分割和单词学习，(2)对新提取的单词的长期记忆，以及(3)婴儿的词形表征将变得更加健壮和具体。拟议项目的结果将促进我们对规范语言发展背后的学习机制的理解。由于各种感觉、神经或发育方面的原因，在面对现实世界的学习挑战时，不太擅长追踪和表现统计规律的人，可能会面临更大的非典型语言发展风险。这项拟议的研究结果将被用来帮助生成和测试关于非典型人群中特定语言延迟的因果机制的假设，例如听力损失的婴儿或由于各种原因在关键发育时期接受次优语言输入的婴儿。

 DESCRIPTION (provided by applicant): Typically developing infants acquire language at a remarkable rate despite numerous perceptual and cognitive challenges. Infants may begin to learn language by tracking regularities in their environment. Specifically, research suggests that infants possess powerful computational mechanisms that may support the segmentation of words from fluent speech and facilitate word learning. The problem is that there is little research on the extent to which statistical regularities support early language acquisition under the challenging learning conditions often faced by young infants. The objective of the proposed research is to advance integrative and comprehensive theories of infant language acquisition by assessing how statistical learning supports (1) speech segmentation and word learning in background noise, (2) infants' ability to encode lexical representations in long-term memory, and (3) infants' abilities to represent newly segmented words with the appropriate level and type of detail to facilitate subsequent language learning. Three Aims will be addressed across nine experiments designed to test how statistical regularities found in natural language input support resilience, longevity, and representational specificity within a developmental framework. Infants will be familiarized with a short natural Italian language corpus and then tested on their ability o either discriminate words that have strong versus weak internal co-occurrence patterns (8- and 11-month-olds), or associate those words with novel objects (17-month-olds). Experiments are designed to tests how infants cope with simultaneous learning challenges. We will test the predictions that strong syllable co-occurrence patterns will bolster (1) speech segmentation and word learning in noise and (2) long-term memory for newly extracted words, and (3) that infants' word form representations will become more robust and specific. Results from the proposed project will advance our understanding of the learning mechanisms underlying normative language development. Individuals who are, for a variety of sensory, neurological, or developmental reasons, less adept at tracking and representing statistical regularities when faced with real-world learning challenges may be at greater risk for atypical language development. Results from the proposed research will be used to help generate and test hypotheses about the causal mechanisms for specific language delays in atypical populations, such as for infants with hearing loss or infants who, for various reasons, receive sub-optimal language input during critical developmental periods.