Variability in Pragmatic Inferencing

为了成功地交流，说话者和听话者必须使用的不仅仅是他们共同语言的知识。通常，理解说话人的意图需要“读字里行间”，从而丰富说话人所说的话的语言意义。例如，如果一个说话者说“我喜欢我的一些亲戚”，听者很可能会理解她在暗示她不喜欢所有的人，即使她的话严格来说是真的，如果她确实喜欢他们。先前的研究表明，听者可以极其迅速地计算出类似丰富的意思。本项目详细考察了说话者（或读者）如何获得如此丰富的意义。听者对说话人的语言表达选择有什么样的期待？听者是否考虑到说话者的交际目的或交际能力？人们在多大程度上可以将更多基于社会的对典型交际行为的期望与语言意义结合起来，这方面存在个体差异吗？语言结构或语境的某些方面是否使听者/读者更容易理解丰富的含义？本项目将探讨目前在理论语言学、哲学和认知心理学中关于丰富意义的本质及其与纯粹语言意义的关系的一些激烈争论。它将首次提供这一领域的个体差异研究，为未来非典型人群（尤其是自闭症患者）的研究奠定基础。这些结果也可能引起计算语言学家的兴趣。

In order to successfully communicate, speakers and hearers must use more than their knowledge of a common language. Often, understanding a speaker's intended meaning requires "reading between the lines" thereby enriching the linguistic meaning of what the speaker has said. For example, if a speaker says "I like some of my relatives," the hearer will likely understand her to have implied that she does not like all of them, even though her utterance is, strictly speaking, true if she does in fact like them. Previous work has shown that similarly enriched meanings can be computed extremely rapidly by hearers. This project examines in detail how speakers (or readers) arrive at such enriched meanings. What kinds of expectations about the speaker's choice of linguistic expressions does the hearer rely on? Does the hearer take into account the speaker's communicative goal or communicative abilities? Are there individual differences in the extent to which people can integrate more socially-based expectations about typical communicative behavior with linguistic meanings? And are there aspects of linguistic structure or context that make enriched meanings more accessible to the hearer/reader? This project will address some currently heated debates in theoretical linguistics, philosophy and cognitive psychology about the nature of enriched meanings and their relationship to purely linguistic meanings. It will provide the first study of individual differences in this domain, laying the groundwork for future studies with atypical populations (especially autistic individuals). The results are also likely of interest to computational linguists.