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Disfluencies, language comprehension, and Tree Adjoining Grammars

机译:流离失所,语言理解和树木邻接文法

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Disfluencies include editing terms such as uh and um as well as repeats and revisions. Little is known about how disfluencies are processed, and there has been next to no research focused on the way that disfluencies affect structure-building operations during comprehension. We review major findings from both computational linguistics and psycholinguistics, and then we summarize the results of our own work which centers on how the parser behaves when it encounters a disfluency. We describe some new research showing that information associated with misarticulated verbs lingers, and which adds to the large body of data on the critical influence of verb argument structures on sentence comprehension. The paper also presents a model of disfluency processing. The parser uses a Tree Adjoining Grammar to build phrase structure. In this approach, filled and unfilled pauses affect the timing of Substitution operations. Repairs and corrections are handled by a mechanism we term "Overlay," which allows the parser to overwrite an undesired tree with the appropriate, correct tree. This model of disfluency processing highlights the need for the parser to sometimes coordinate the mechanisms that perform garden-path reanalysis with those that do disfluency repair. The research program as a whole demonstrates that it is possible to study disfluencies systematically and to learn how the parser handles filler material and mistakes. It also showcases the power of Tree Adjoining Grammars, a formalism developed by Aravind Joshi which has yielded results in many different areas of linguistics and cognitive science.
机译:不满意之处包括编辑字词(例如uh和um)以及重复和修订。人们对如何处理水气知之甚少,并且几乎没有研究关注水气在理解过程中如何影响结构建造操作。我们回顾了计算语言学和心理语言学的主要发现,然后总结了我们自己的工作结果,这些工作的重点是解析器在遇到不满意时的行为方式。我们描述了一些新的研究,表明与错位动词相关的信息会持续存在,这增加了关于动词自变量结构对句子理解的关键影响的大量数据。本文还提出了一种水流处理模型。解析器使用树状邻接语法构建短语结构。在这种方法中,填充和未填充的暂停都会影响替换操作的时间。修复和更正通过一种我们称为“覆盖”的机制进行处理,该机制允许解析器使用适当的正确树覆盖不希望的树。这种差异处理模型强调了解析器有时需要将进行花园路径重新分析的机制与进行差异修复的机制进行协调。整个研究程序表明,可以系统地研究差异性,并了解解析器如何处理填充材料和错误。它还展示了Aravind Joshi开发的形式化树“ Tree Adjoining Grammrs”的功能,该语言已在语言学和认知科学的许多不同领域产生了成果。

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