Probabilistic Grammars as Models of Gradience in Language Processing
Probabilistic Grammars as Models of Gradience in Language Processing
复制标题
概率语法作为语言处理中的梯度模型
DOI：
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复制
发表时间：
2006
期刊：
影响因子：
--
通讯作者：
Frank Keller
中科院分区：
文献类型：
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作者：
M. Crocker;Frank Keller
本文涉及人类句子处理中的渐变。我们回顾了经验在指导句子处理器决定中的作用的实验证据。基于这一证据，我们认为在处理某些句法结构中观察到的梯度b ehavior可以追溯到处理器对这些结构所具有的过去经验。用建模术语，可以使用大型，平衡的Cor Pora近似语言经验。我们概述了基于语料库的文献模型，这些模型利用了这一事实，因此可以很好地将梯度预测作为回合处理行为。最后，我们讨论了许多问题，即句子处理中的渐变与梯度语法之间的关系，并得出结论，应以概念和建模术语分别处理这两种现象。
This article deals with gradience in human sentence processing. We review the experimental evidence for the role of experience in guiding the decisions o f the sentence processor. Based on this evidence, we argue that the gradient b ehavior observed in the processing of certain syntactic constructions can be traced back to th e amount of past experience that the processor has had with these constructions . In modeling terms, linguistic experience can be approximated using large, balanced cor pora. We give an overview of corpus-based and probabilistic models in the literature that have exploited this fact, and hence are well placed to make gradient predictions a bout processing behavior. Finally, we discuss a number of questions regard ing the relationship between gradience in sentence processing and gradient grammaticality, and come to the conclusion that these two phenomena should be treated separately in conceptual and modeling terms.
DOI：
10.1037/0278-7393.19.3.528
发表时间：
1993-05-01
影响因子：
2.6
作者：
TRUESWELL, JC;TANENHAUS, MK;KELLO, C
通讯作者：
KELLO, C