基于学习的语音层级解释

IF 1.6 1区 文学 0 LANGUAGE & LINGUISTICS Linguistic Inquiry Pub Date : 2024-03-07 DOI:10.1162/ling_a_00530
Caleb Belth
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引用次数: 0

摘要

语音交替常常涉及相邻音段之间的依存关系。尽管在辅音和元音和谐交替中,相关音段之间的距离很明显,但在层级表征中,这些依赖关系通常可以被视为相邻的。然而,使相邻依赖关系相邻所需的层级在跨语言上是不同的,而且层级表征与平面的字符串式表征相比具有抽象性,这使得语音学家们开始寻求在语音学理论中使用层级表征的理由。在本文中,我提出了一种基于学习的层状表征解释。我认为人类倾向于追踪相邻项目之间的依赖关系,并提出了一种简单的学习算法,通过只追踪相邻的依赖关系来整合这种倾向。该模型在无法预测交替片段的表面形式时会改变表征--这是由容忍原则(Tolerance Principle)决定的,该原则允许在自然数据不可避免的稀疏性和例外情况下进行学习。在这种学习过程中,自然而然地产生了层级式表征,当在少量自然语言数据上进行训练时,该模型在泛化到保持不变的测试词上时达到了很高的准确性,同时还能灵活处理跨语言的复杂性,如中性句段和阻塞词。该模型还能精确预测人类的泛化行为,这些预测在人工语言实验中也得到了证实。
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A Learning-Based Account of Phonological Tiers
Morphophonological alternations often involve dependencies between adjacent segments. Despite the apparent distance between relevant segments in the alternations that arise in consonant and vowel harmony, these dependencies can usually be viewed as adjacent on a tier representation. However, the tier needed to render dependencies adjacent varies crosslinguistically, and the abstract nature of tier representations in comparison to flat, string-like representations has led phonologists to seek justification for their use in phonological theory. In this paper, I propose a learning-based account of tier-like representations. I argue that humans show a proclivity for tracking dependencies between adjacent items, and propose a simple learning algorithm that incorporates this proclivity by tracking only adjacent dependencies. The model changes representations in response to being unable to predict the surface form of alternating segments—a decision governed by the Tolerance Principle, which allows for learning despite the sparsity and exceptions inevitable in naturalistic data. Tier-like representations naturally emerge from this learning procedure, and, when trained on small amounts of natural language data, the model achieves high accuracy generalizing to held-out test words, while flexibly handling cross-linguistic complexities like neutral segments and blockers. The model also makes precise predictions about human generalization behavior, and these are consistently borne out in artificial language experiments.
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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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