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语言输入的序列性质对句子复杂性的影响。

Consequences of the serial nature of linguistic input for sentenial complexity.

机构信息

Brown UniversityMassachusetts Institute of Technology.

出版信息

Cogn Sci. 2005 Mar 4;29(2):261-90. doi: 10.1207/s15516709cog0000_7.

DOI:10.1207/s15516709cog0000_7
PMID:21702774
Abstract

All other things being equal the parser favors attaching an ambiguous modifier to the most recent possible site. A plausible explanation is that locality preferences such as this arise in the service of minimizing memory costs-more distant sentential material is more difficult to reactivate than more recent material. Note that processing any sentence requires linking each new lexical item with material in the current parse. This often involves the construction of long-distance dependencies. Under a resource-limited view of language processing, lengthy integrations should induce difficulty even in unambiguous sentences. To date there has been little direct quantitative evidence in support of this perspective. This article presents 2 self-paced reading studies, which explore the hypothesis that dependency distance is a fundamental determinant of reading complexity in unambiguous constructions in English. The evidence suggests that the difficulty associated with integrating a new input item is heavily determined by the amount of lexical material intervening between the input item and the site of its target dependents. The patterns observed here are not straightforwardly accounted for within purely experience-based models of complexity. Instead, this work supports the role of a memory bottleneck in language comprehension. This constraint arises because hierarchical linguistic relations must be recovered from a linear input stream.

摘要

所有其他条件相同的情况下,解析器更倾向于将一个模棱两可的修饰语附加到最近的可能位置。一个合理的解释是,这种局部性偏好是为了最小化内存成本而产生的——距离句子材料越远,重新激活就越困难,比最近的材料更困难。请注意,处理任何句子都需要将每个新的词汇项与当前解析中的材料联系起来。这通常涉及构建远距离依赖关系。在语言处理的资源有限观点下,即使在非歧义句子中,长时间的整合也应该会引起困难。到目前为止,几乎没有直接的定量证据支持这一观点。本文提出了 2 项自我调整阅读研究,探讨了依赖距离是英语中明确结构阅读复杂性的基本决定因素的假设。证据表明,与整合新输入项相关的困难在很大程度上取决于输入项和目标依赖项所在位置之间的词汇材料量。这里观察到的模式不能简单地用基于经验的复杂性模型来解释。相反,这项工作支持记忆瓶颈在语言理解中的作用。这种约束是因为层次语言关系必须从线性输入流中恢复。

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