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当冗余有用时:一种贝叶斯方法处理“过度信息”的指称表达。

When redundancy is useful: A Bayesian approach to "overinformative" referring expressions.

机构信息

Department of Psychology, Stanford University.

Institute for Cognitive Science, Osnabruck University.

出版信息

Psychol Rev. 2020 Jul;127(4):591-621. doi: 10.1037/rev0000186. Epub 2020 Apr 2.

Abstract

Referring is one of the most basic and prevalent uses of language. How do speakers choose from the wealth of referring expressions at their disposal? Rational theories of language use have come under attack for decades for not being able to account for the seemingly irrational overinformativeness ubiquitous in referring expressions. Here we present a novel production model of referring expressions within the Rational Speech Act framework that treats speakers as agents that rationally trade off cost and informativeness of utterances. Crucially, we relax the assumption that informativeness is computed with respect to a deterministic Boolean semantics, in favor of a nondeterministic continuous semantics. This innovation allows us to capture a large number of seemingly disparate phenomena within one unified framework: the basic asymmetry in speakers' propensity to overmodify with color rather than size; the increase in overmodification in complex scenes; the increase in overmodification with atypical features; and the increase in specificity in nominal reference as a function of typicality. These findings cast a new light on the production of referring expressions: rather than being wastefully overinformative, reference is usefully redundant. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

摘要

指称是语言最基本和最常见的用途之一。说话者如何从他们可用的丰富指称表达中进行选择?几十年来,语言使用的理性理论一直受到攻击,因为它们无法解释在指称表达中普遍存在的看似不合理的过度信息量。在这里,我们在理性言语行为框架内提出了一种新的指称表达生成模型,将说话者视为理性权衡话语成本和信息量的主体。至关重要的是,我们放宽了信息量是根据确定性布尔语义计算的假设,转而采用非确定性连续语义。这一创新使我们能够在一个统一的框架内捕捉到大量看似不同的现象:说话者倾向于用颜色而不是大小过度修饰的基本不对称性;复杂场景中过度修饰的增加;非典型特征的过度修饰的增加;以及作为典型性函数的名词参考的特异性的增加。这些发现为指称表达的生成提供了新的视角:指称不是浪费性的过度信息量,而是有用的冗余。

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