Statistical approaches to linguistic pattern learning

描述(由申请人提供)：本研究的目的是对影响婴儿、儿童和成人如何从语言输入的分布信息中学习其母语类别的因素进行全面的说明。语言的类别由在语法句子中扮演等同功能的词(例如，名词、动词)的集合组成。分布信息是指成分在大型句子语料库中的模式，包括这些成分出现的频率、它们在句子中的位置以及相邻成分提供的上下文。我们关于分词中统计学习(学习者如何确定哪些声音序列构成单词)的长期研究计划记录了婴儿、儿童和成年人对复杂分布信息的能力、快捷性和健壮性。在这里，我们将研究计划扩展到学习高级语言结构的一个关键方面。在我们提出的研究中，我们使用了一种微型人工语言范式，使我们能够完全控制输入中的所有分布线索，这在真实语言中几乎是不可能的。参与者听一段话语样本，并对其可接受性做出判断。至关重要的是，在学习阶段，他们听不到人工语言中所有可能的“合法”话语；有些话语被扣留，以便在以后的后测中使用。测试后的话语要么符合学习阶段存在的分布模式，要么违反这些模式。关键的测试是参与者是否判断新奇但合法的话语是可接受的，从而显示出超越他们所接触到的输入的正确概括的能力。对儿童的研究通过将话语与简单事件的视频配对，为学习分配线索提供了额外的支持。对成年人的研究将用于比较，还将向他们提供视觉-运动领域的学习材料，以评估详细的学习时间过程和结果对听觉语言材料的特异性。综上所述，这些对婴儿、儿童和成人的研究结果将证明语言学习中的关键结构变量，这些变量使类别形成的分布机制得以运作，并将突出这些机制可能因年龄和领域而不同的方式。公共卫生相关性：语言发展是人类物种的标志之一，但由于早期接触不同数量的语言输入存在巨大差异，因此很难对其进行研究。使用实验室在几个小时内获得的人工语言，为了解语言发展的机制提供了一个窗口。我们将在实验室中研究语言学习，以获得一个独特的视角，了解类别(名词、动词等)是如何通过听一小段句子中的单词模式来形成的。这些研究不仅将揭示语言学习的基本机制，而且还将建立可以比较语言延迟的基准。此外，了解导致正常儿童成功习得的机制有助于确定语言障碍的位置，并设计治疗障碍的方法。

DESCRIPTION (provided by applicant): The purpose of the proposed research is to provide a comprehensive account of the factors that affect how infants, children, and adults learn the categories of their native language from distributional information in linguistic input. The categories of a language consist of sets of words (e.g., noun, verb) that play a functionally equivalent role in grammatical sentences. Distributional information refers to the patterning of elements in a large corpus of sentences and includes how frequently those elements occur, what position they occupy in a sentence, and the context provided by neighboring elements. Our longstanding program of research on statistical learning in word segmentation (how learners determine which sound sequences form words) has documented the power, rapidity, and robustness of infants, children, and adults sensitivity to complex distributional information. Here we extend that program of research to a crucial aspect of learning higher-level structures of language. In our proposed studies, we use a miniature artificial language paradigm that affords us complete control over all the distributional cues in the input, something that is virtually impossible using real languages. Participants listen to a sample of utterances and make judgments about their acceptability. Crucially, during a learning phase, they do not hear all possible utterances that are "legal" in the artificial language; some are withheld for use in a later post-test. The post-test utterances either conform to the distributional patterns present in the learning phase, or they violate those patterns. The key test is whether participants judge novel-but-legal utterances to be acceptable, thereby showing the ability to generalize correctly beyond the input to which they were exposed. Studies of children provide additional support for learning the distributional cues by pairing utterances with videos of simple events. Studies of adults will be used for comparison, and will also present them with learning materials in the visual-motor domain to assess the detailed time-course of learning and the specificity of the results to auditory linguistic materials. Taken together, the results of these studies of infants, children, and adults will document the key structural variables in language learning that enable a distributional mechanism of category formation to operate and will highlight the ways these mechanisms may differ over age and domain. PUBLIC HEALTH RELEVANCE: Language development is one of the hallmarks of the human species, yet it is difficult to study because of the huge variation in early exposure to different amounts of linguistic input. The use of artificial languages that are acquired in the lab over a few hours provides a window on the mechanisms of language development. We will study language learning in the lab to gain a unique perspective on how the categories (noun, verb, etc) are formed from listening to the patterns of words in a small set of sentences. These studies will not only reveal a basic mechanism of language learning, but also establish benchmarks against which language delay can be compared. Moreover, understanding the mechanisms that lead to successful acquisition in normal children can help to identify loci of language disorders and design methods for remediating disorders.