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从被动语音感知到语音产生的统计学习迁移。

Transfer of statistical learning from passive speech perception to speech production.

机构信息

Department of Psychology, Carnegie Mellon University, Baker Hall, Floor 3, Frew St, Pittsburgh, PA, 15213, USA.

Center for the Neural Basis of Cognition, Pittsburgh, PA, 15213, USA.

出版信息

Psychon Bull Rev. 2024 Jun;31(3):1193-1205. doi: 10.3758/s13423-023-02399-8. Epub 2023 Oct 26.

Abstract

Communicating with a speaker with a different accent can affect one's own speech. Despite the strength of evidence for perception-production transfer in speech, the nature of transfer has remained elusive, with variable results regarding the acoustic properties that transfer between speakers and the characteristics of the speakers who exhibit transfer. The current study investigates perception-production transfer through the lens of statistical learning across passive exposure to speech. Participants experienced a short sequence of acoustically variable minimal pair (beer/pier) utterances conveying either an accent or typical American English acoustics, categorized a perceptually ambiguous test stimulus, and then repeated the test stimulus aloud. In the canonical condition, /b/-/p/ fundamental frequency (F0) and voice onset time (VOT) covaried according to typical English patterns. In the reverse condition, the F0xVOT relationship reversed to create an "accent" with speech input regularities atypical of American English. Replicating prior studies, F0 played less of a role in perceptual speech categorization in reverse compared with canonical statistical contexts. Critically, this down-weighting transferred to production, with systematic down-weighting of F0 in listeners' own speech productions in reverse compared with canonical contexts that was robust across male and female participants. Thus, the mapping of acoustics to speech categories is rapidly adjusted by short-term statistical learning across passive listening and these adjustments transfer to influence listeners' own speech productions.

摘要

与带有不同口音的说话者交流可能会影响自己的说话方式。尽管语音感知产生转移的证据很强,但转移的性质仍然难以捉摸,对于在说话者之间转移的声学特性以及表现出转移的说话者的特征,结果各不相同。本研究通过被动聆听语音时的统计学习来研究感知产生转移。参与者经历了一个短暂的、声学上可变的最小对(beer/pier)话语序列,这些话语传达了口音或典型的美国英语口音,对感知上模棱两可的测试刺激进行分类,然后大声重复测试刺激。在典型条件下,/b/-/p/基频(F0)和嗓音起始时间(VOT)根据典型英语模式协变。在反转条件下,F0xVOT 关系反转,用语音输入的规则创建一个“口音”,这些规则与美国英语的典型规则不同。与之前的研究一致,在反转的典型统计环境中,F0 在感知语音分类中所起的作用较小。至关重要的是,这种权重转移到了产生中,在反转的情况下,听众自己的语音产生中 F0 被系统地加权,这种情况在男性和女性参与者中都是稳健的。因此,通过被动聆听进行的短期统计学习可以快速调整语音与语音类别的映射,这些调整会转移到影响听众自己的语音产生中。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/de8f/11192850/f2ffb062a960/13423_2023_2399_Fig1_HTML.jpg

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