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一种用于韵律音系学的计算学习模型。

A computational learning model for metrical phonology.

作者信息

Dresher B E, Kaye J D

机构信息

Department of Linguistics, University of Toronto, Ontario, Canada.

出版信息

Cognition. 1990 Feb;34(2):137-95. doi: 10.1016/0010-0277(90)90042-i.

Abstract

One of the major challenges to linguistic theory is the solution of what has been termed the "projection problem". Simply put, linguistics must account for the fact that starting from a data base that is both unsystematic and relatively small, a human child is capable of constructing a grammar that mirrors, for all intents and purposes, the adult system. In this article we shall address ourselves to the question of the learnability of a postulated subsystem of phonological structure: the stress system. We shall describe a computer program which is designed to acquire this subpart of linguistic structure. Our approach follows the "principles and parameters" model of Chomsky (1981a, b). This model is particularly interesting from both a computational point of view and with respect to the development of learning theories. We encode the relevant aspects of universal grammar (UG)--those aspects of linguistic structure that are presumed innate and thus present in every linguistic system. The learning process consists of fixing a number of parameters which have been shown to underlie stress systems and which should, in principle, lead the learner to the postulation of the system from which the primary linguistic data (i.e., the input to the learner) is drawn. We go on to explore certain formal and substantive properties of this learning system. Questions such as cross-parameter dependencies, determinism, subsets, and incremental versus all-at-once learning are raised and discussed in the article. The issues raised by this study provide another perspective on the formal structure of stress systems and the learnability of parameter systems in general.

摘要

语言理论面临的主要挑战之一是解决所谓的“投射问题”。简单来说,语言学必须解释这样一个事实:人类儿童从一个既无系统又相对较小的数据库出发,却能够构建出一种在所有意图和目的上都能反映成人语言系统的语法。在本文中,我们将探讨一个假设的音系结构子系统——重音系统的可学习性问题。我们将描述一个旨在获取语言结构这一子部分的计算机程序。我们的方法遵循乔姆斯基(1981a,b)的“原则与参数”模型。从计算角度以及学习理论的发展来看,这个模型都特别有趣。我们对普遍语法(UG)的相关方面进行编码——即那些被认为是先天的、因而存在于每一个语言系统中的语言结构方面。学习过程包括确定一些参数,这些参数已被证明是重音系统的基础,并且原则上应该引导学习者推测出产生主要语言数据(即学习者的输入)的系统。我们接着探讨这个学习系统的某些形式和实质属性。诸如跨参数依赖、确定性、子集以及增量式学习与一次性学习等问题在本文中被提出并讨论。这项研究提出的问题为一般重音系统的形式结构和参数系统的可学习性提供了另一个视角。

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