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语音处理中的睡眠驱动计算

Sleep-Driven Computations in Speech Processing.

作者信息

Frost Rebecca L A, Monaghan Padraic

机构信息

Department of Psychology, Lancaster University, Lancaster, United Kingdom.

出版信息

PLoS One. 2017 Jan 5;12(1):e0169538. doi: 10.1371/journal.pone.0169538. eCollection 2017.

Abstract

Acquiring language requires segmenting speech into individual words, and abstracting over those words to discover grammatical structure. However, these tasks can be conflicting-on the one hand requiring memorisation of precise sequences that occur in speech, and on the other requiring a flexible reconstruction of these sequences to determine the grammar. Here, we examine whether speech segmentation and generalisation of grammar can occur simultaneously-with the conflicting requirements for these tasks being over-come by sleep-related consolidation. After exposure to an artificial language comprising words containing non-adjacent dependencies, participants underwent periods of consolidation involving either sleep or wake. Participants who slept before testing demonstrated a sustained boost to word learning and a short-term improvement to grammatical generalisation of the non-adjacencies, with improvements after sleep outweighing gains seen after an equal period of wake. Thus, we propose that sleep may facilitate processing for these conflicting tasks in language acquisition, but with enhanced benefits for speech segmentation.

摘要

习得语言需要将语音分割成单个单词,并对这些单词进行抽象以发现语法结构。然而,这些任务可能相互冲突——一方面需要记忆语音中出现的精确序列,另一方面需要对这些序列进行灵活重构以确定语法。在此,我们研究语音分割和语法泛化是否能同时发生——睡眠相关的巩固过程能否克服这些任务的冲突要求。在接触一种由包含非相邻依存关系单词的人工语言后,参与者经历了包括睡眠或清醒的巩固阶段。在测试前睡眠的参与者在单词学习方面有持续提升,并且对非相邻关系的语法泛化有短期改善,睡眠后的改善超过了同等时长清醒后的收获。因此,我们提出睡眠可能有助于语言习得中这些相互冲突任务的处理,但对语音分割的益处更大。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5b1e/5215958/ca42fa5995a3/pone.0169538.g001.jpg

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