Consequences of the serial nature of linguistic input for sentenial complexity
Consequences of the serial nature of linguistic input for sentenial complexity
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DOI：
10.1207/s15516709cog0000_7
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发表时间：
2005-03-01
影响因子：
2.5
通讯作者：
Gibson, E
中科院分区：
文献类型：
--
作者：
Grodner, D;Gibson, E
在所有其他条件相同的情况下，解析器倾向于向最近可能的站点附加一个模棱两可的修饰符。一个看似合理的解释是，这样的位置偏好是为了最小化记忆成本--较远的句子材料比较新的材料更难重新激活。请注意，处理任何句子都需要将每个新词条与当前语法分析中的材料相关联。这通常涉及构建远程依赖关系。在语言处理的资源有限的观点下，冗长的整合即使在没有歧义的句子中也会造成困难。到目前为止，几乎没有直接的定量证据支持这一观点。本文介绍了两项自定进度的阅读研究，探讨了依赖距离是英语无歧义结构中阅读复杂性的根本决定因素这一假设。证据表明，整合一个新的输入项的难度在很大程度上取决于输入项和其目标从属项之间的词汇量。这里观察到的模式不能直接在纯粹基于经验的复杂性模型中解释。相反，这项研究支持了记忆瓶颈在语言理解中的作用。这种约束的出现是因为层级语言关系必须从线性输入流中恢复。
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.