Denby Thomas, Schecter Jeffrey, Arn Sean, Dimov Svetlin, Goldrick Matthew
Department of Linguistics, Northwestern University.
J Exp Psychol Learn Mem Cogn. 2018 Feb;44(2):280-294. doi: 10.1037/xlm0000465. Epub 2017 Sep 21.
Phonotactics-constraints on the position and combination of speech sounds within syllables-are subject to statistical differences that gradiently affect speaker and listener behavior (e.g., Vitevitch & Luce, 1999). What statistical properties drive the acquisition of such constraints? Because they are naturally highly correlated, previous work has been unable to dissociate the contribution of 2 properties: contextual variability (the number of unique phonological contexts in which a phonotactic pattern appears) and exemplar strength (the overall number of times the pattern appears). Using an artificial language learning paradigm, 3 experiments disentangled the effects of variability and strength, indexed by type and token frequency, respectively, on the learning of gradient phonotactics. When the 2 factors were decorrelated (Experiment 2), participants showed greater generalization of patterns advantaged for contextual variability, but not those advantaged for exemplar strength. When the 2 factors were anticorrelated (Experiment 3), participants preferred patterns advantaged in contextual variability, even though they were disadvantaged for exemplar strength. These results suggest that contextual variability is the key force driving phonotactic learning, as it allows learners to home in on the invariant features of the input. (PsycINFO Database Record
音位结构规则——关于音节内语音位置和组合的限制——存在统计差异，这些差异会逐步影响说话者和听者的行为（例如，维特维奇和卢斯，1999）。哪些统计特性驱动了此类限制的习得？由于它们自然高度相关，以往的研究无法区分两种特性的作用：语境变异性（音位结构模式出现的独特语音语境数量）和样例强度（该模式出现的总次数）。使用人工语言学习范式，三项实验分别通过类型频率和标记频率来区分变异性和强度对渐变音位结构学习的影响。当这两个因素去相关时（实验2），参与者对在语境变异性方面占优势的模式表现出更大的泛化能力，但对在样例强度方面占优势的模式则不然。当这两个因素反相关时（实验3），参与者更喜欢在语境变异性方面占优势的模式，即使它们在样例强度方面处于劣势。这些结果表明，语境变异性是驱动音位结构学习的关键因素，因为它使学习者能够聚焦于输入中的不变特征。（《心理学文摘数据库记录》 ）
