On the role of locality in learning stress patterns*
On the role of locality in learning stress patterns*
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关于局部性在学习压力模式中的作用*
DOI：
10.1017/s0952675709990145
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发表时间：
2009
期刊：
影响因子：
1.3
通讯作者：
Jeffrey Heinz
中科院分区：
文献类型：
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作者：
Jeffrey Heinz
摘要本文提出了一个以前没有注意到的世界语言的压力模式的普遍属性：他们是，小街区，邻里不同。邻域独特性是自动机理论术语中定义的局部性条件。这一普遍性是通过考察两个类型学研究中所包含的重音模式而建立的。引人注目的是，许多逻辑上可能的（但未经证实的）模式不具有此属性。邻里独特性不仅以一种非平凡的方式将已证明的模式结合起来，它还自然地提供了一种归纳原则，允许学习者从有限的数据中进行归纳。一个学习算法，概括未能区分相同的邻居环境中学习者的语言输入-因此学习邻里不同的模式-以及几乎每一个压力模式的类型学。通过这种方式，这项工作支持的想法，学习者的属性可以解释某些属性的证明类型学，一个想法不直截了当地在最优理论和原则和参数框架。
Abstract This paper presents a previously unnoticed universal property of stress patterns in the world's languages: they are, for small neighbourhoods, neighbourhood-distinct. Neighbourhood-distinctness is a locality condition defined in automata-theoretic terms. This universal is established by examining stress patterns contained in two typological studies. Strikingly, many logically possible – but unattested – patterns do not have this property. Not only does neighbourhood-distinctness unite the attested patterns in a non-trivial way, it also naturally provides an inductive principle allowing learners to generalise from limited data. A learning algorithm is presented which generalises by failing to distinguish same-neighbourhood environments perceived in the learner's linguistic input – hence learning neighbourhood-distinct patterns – as well as almost every stress pattern in the typology. In this way, this work lends support to the idea that properties of the learner can explain certain properties of the attested typology, an idea not straightforwardly available in optimality-theoretic and Principle and Parameter frameworks.
DOI：
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发表时间：
2000
期刊：
--
影响因子：
--
作者：
Dan Jurafsky;James H. Martin
通讯作者：
Dan Jurafsky;James H. Martin