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人类学习者能够学习任意的语言结构吗?

Are Human Learners Capable of Learning Arbitrary Language Structures.

作者信息

Lin Yu-Leng

机构信息

Department of Foreign Languages and Literature, Feng Chia University, Taichung 407102, Taiwan.

出版信息

Brain Sci. 2023 Jan 21;13(2):181. doi: 10.3390/brainsci13020181.

Abstract

The artificial grammar learning paradigm is a classic method of investigating the influence of universal constraints on shaping learning biases on language acquisition. While this method has been used extensively by linguists to test theoretical claims in generative grammar, one of the most prevalent frameworks in language acquisition, several studies have questioned whether artificial grammar learning reflects language acquisition enough to allow us to use it to draw inferences about the validity of universal constraints, particularly those arising from phonetic naturalness. The current study tests whether artificial grammar learning shows the effect of one robust phonetic naturalness constraint: the restriction on nasal harmony patterns arising from the sonority hierarchy. Nasal harmony is of particular interest because it is one of the few types of harmony that occurs between consonants and vowels, which is an under-researched topic. The results, contrary to the skeptical concerns, showed that participants ( = 120) could learn an artificial grammar involving a natural pattern, but could not learn one corresponding to an arbitrary/phonetically unmotivated pattern in the same way or to the same degree. This study contributes epistemic support to the large body of work using artificial grammar experiments to test phonological operations.

摘要

人工语法学习范式是一种经典方法,用于研究普遍限制对塑造语言习得学习偏差的影响。虽然语言学家广泛使用这种方法来检验生成语法中的理论主张(生成语法是语言习得中最流行的框架之一),但一些研究质疑人工语法学习是否足以反映语言习得,从而使我们能够利用它来推断普遍限制的有效性,特别是那些源于语音自然性的限制。本研究测试人工语法学习是否显示出一种强大的语音自然性限制的效果:即由响度层级产生的对鼻韵和谐模式的限制。鼻韵和谐特别值得关注,因为它是辅音和元音之间出现的少数几种和谐类型之一,而这是一个研究不足的主题。结果与怀疑论者的担忧相反,表明参与者((n = 120))能够学习包含自然模式的人工语法,但无法以相同方式或相同程度学习对应于任意/语音无动机模式的人工语法。这项研究为使用人工语法实验来测试音系操作的大量工作提供了认知支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/575c/9954588/094f7f0fe118/brainsci-13-00181-g001.jpg

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