使用计算模型测试语法可学习性

IF 1.6 1区 文学 0 LANGUAGE & LINGUISTICS
Ethan Gotlieb Wilcox;Richard Futrell;Roger Levy
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引用次数: 0

摘要

我们通过评估自回归(增量)语言模型(使用深度学习来预测给定前面上下文的下一个单词)的泛化,研究了英语填空依赖性的可学习性和对它们的“孤岛”约束。利用实验心理语言学启发的析因测试,我们发现模型不仅获得了填充物和间隙之间的基本偶然性,而且还获得了依赖关系中隐含的无界性和分层约束。我们通过证明其对填充-间隙偶然性的期望在岛屿环境中衰减来评估模型对岛屿约束的获取。我们的研究结果为这种特殊结构提供了反对“刺激的贫困”论点的经验证据。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Using Computational Models to Test Syntactic Learnability
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来源期刊
Linguistic Inquiry
Linguistic Inquiry Multiple-
CiteScore
2.50
自引率
12.50%
发文量
54
期刊介绍: Linguistic Inquiry leads the field in research on current topics in linguistics. This key resource explores new theoretical developments based on the latest international scholarship, capturing the excitement of contemporary debate in full-scale articles as well as shorter contributions (Squibs and Discussion) and more extensive commentary (Remarks and Replies).
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