Conwell Erin, Snedeker Jesse
Department of Psychology, North Dakota State University.
Department of Psychology, Harvard University.
Lang Learn Dev. 2024;20(4):364-379. doi: 10.1080/15475441.2024.2342873. Epub 2024 Apr 20.
Natural languages contain systematic relationships between verb meaning and verb argument structure. Artificial language learning studies typically remove those relationships and instead pair verb meanings randomly with structures. Adult participants in such studies can detect statistical regularities associated with words in these languages and their use of novel words will adhere to those statistical regularities. However, word use in natural languages is associated with more than distributional statistics. Using an artificial language learning paradigm, we asked how a relationship between verb meaning and sentence structure affected learning and structure generalization. Twenty-four English-speaking adults watched videos described in an artificial language with two possible sentence structures. Half of the participants (statistics-only condition) learned a language with no relationship between verb meaning and sentence structure. The other half (semantics condition) learned a language in which verb meaning predicted which structures a verb occurred in. Although all learners were able to comprehend the learned structures with novel verbs, participants in the semantics conditions made grammaticality judgments and productions with novel verbs that were more consistent with the target language than participants in the statistics-only condition. The availability of semantic cues to verb subcategory supports artificial language learning.
自然语言中动词意义和动词论元结构之间存在系统的关系。人工语言学习研究通常会消除这些关系，而是将动词意义与结构随机配对。此类研究中的成年参与者能够检测出与这些语言中的单词相关的统计规律，并且他们对新单词的使用将遵循这些统计规律。然而，自然语言中的单词使用不仅仅与分布统计相关。我们采用人工语言学习范式，探究动词意义和句子结构之间的关系如何影响学习和结构泛化。24名说英语的成年人观看了用一种具有两种可能句子结构的人工语言描述的视频。一半的参与者（仅统计条件）学习的语言中动词意义和句子结构之间没有关系。另一半（语义条件）学习的语言中，动词意义能预测动词出现的结构。尽管所有学习者都能够理解带有新动词的所学结构，但语义条件下的参与者对新动词进行的语法性判断和生成比仅统计条件下的参与者更符合目标语言。动词子范畴的语义线索有助于人工语言学习。
