Murphy Timothy K, Nozari Nazbanou, Holt Lori L
Waisman Center, University of Wisconsin-Madison, 1500 Highland Ave, Madison, WI, 53705, USA.
Department of Surgery, University of Wisconsin-Madison, Madison, WI, USA.
Psychon Bull Rev. 2025 Apr 14. doi: 10.3758/s13423-025-02690-w.
Perception changes rapidly and implicitly as a function of passive exposure to speech that samples different acoustic distributions. Past research has shown that this statistical learning generalizes across talkers and, to some extent, new items, but these studies involved listeners' active engagement in processing statistics-bearing stimuli. In this study, we manipulated the relationship between voice onset time (VOT) and fundamental frequency (F0) to establish distributional regularities either aligned with American English or reversed to create a subtle foreign accent. We then tested whether statistical learning across passive exposure to these distributions generalized to new items never experienced in the accent. Experiment 1 showed statistical learning across passive exposure but no generalization of learning when exposure and test items shared the same initial consonant but differed in vowels (bear/pear → beer/pier) or when they differed in initial consonant but shared distributional regularities across VOT and F0 dimensions (deer/tear → beer/pier). Experiment 2 showed generalization to stimuli that shared the statistics-bearing phoneme (bear/pear → beer/pier), but only when the response set included tokens from both exposure and generalization stimuli. Moreover, statistical learning transferred to influence the subtle acoustics of listeners' own speech productions but did not generalize to influence productions of stimuli not heard in the accent. In sum, passive exposure is thus sufficient to support statistical learning and its generalization, but task demands modulate this dynamic. Moreover, production does not simply mirror perception: generalization in perception was not accompanied by transfer to production.
作为被动接触采样不同声学分布的语音的函数，感知会迅速且潜移默化地发生变化。过去的研究表明，这种统计学习可以跨说话者进行概括，并且在一定程度上也可以跨新项目进行概括，但这些研究涉及听众积极参与处理承载统计信息的刺激。在本研究中，我们操纵了语音起始时间（VOT）和基频（F0）之间的关系，以建立与美国英语一致的分布规律，或者将其颠倒以制造一种微妙的外国口音。然后，我们测试了通过被动接触这些分布进行的统计学习是否能推广到从未在这种口音中体验过的新项目。实验1表明，通过被动接触可以进行统计学习，但当接触项目和测试项目共享相同的初始辅音但元音不同时（bear/pear → beer/pier），或者当它们的初始辅音不同但在VOT和F0维度上共享分布规律时（deer/tear → beer/pier），学习没有得到推广。实验2表明，对共享承载统计信息音素的刺激有推广作用（bear/pear → beer/pier），但前提是反应集包括来自接触刺激和推广刺激的样本。此外，统计学习会转移以影响听众自己语音产生的微妙声学特征，但不会推广到影响未在这种口音中听到的刺激的产生。总之，被动接触足以支持统计学习及其推广，但任务要求会调节这种动态过程。此外，产生并不简单地反映感知：感知中的推广并没有伴随着向产生的转移。
