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通过反馈塑造合成语音的感知学习。

Shaping perceptual learning of synthetic speech through feedback.

作者信息

Lehet Matthew I, Fenn Kimberly M, Nusbaum Howard C

机构信息

Department of Psychology, Michigan State Universit, East Lansing, MI, USA.

Department of Psychology, The University of Chicago, Chicago, IL, USA.

出版信息

Psychon Bull Rev. 2020 Oct;27(5):1043-1051. doi: 10.3758/s13423-020-01743-6.

DOI:10.3758/s13423-020-01743-6
PMID:32500520
Abstract

Listeners exposed to accented speech must adjust how they map between acoustic features and lexical representations such as phonetic categories. A robust form of this adaptive perceptual learning is learning to perceive synthetic speech where the connections between acoustic features and phonetic categories must be updated. Both implicit learning through mere exposure and explicit learning through directed feedback have previously been shown to produce this type of adaptive learning. The present study crosses implicit exposure and explicit feedback with the presence or absence of a written identification task. We show that simple exposure produces some learning, but explicit feedback produces substantially stronger learning, whereas requiring written identification did not measurably affect learning. These results suggest that explicit feedback guides learning of new mappings between acoustic patterns and known phonetic categories. We discuss mechanisms that may support learning via implicit exposure.

摘要

接触带有口音的语音的听众必须调整他们在声学特征与词汇表征(如语音类别)之间的映射方式。这种适应性感知学习的一种强大形式是学习感知合成语音,其中声学特征与语音类别之间的联系必须更新。先前已经表明,通过单纯接触进行的隐性学习和通过定向反馈进行的显性学习都会产生这种类型的适应性学习。本研究将隐性接触和显性反馈与是否存在书面识别任务进行了交叉研究。我们发现,单纯接触会产生一些学习效果,但显性反馈会产生更强的学习效果,而要求进行书面识别并不会对学习产生显著影响。这些结果表明,显性反馈指导了声学模式与已知语音类别之间新映射的学习。我们讨论了可能支持通过隐性接触进行学习的机制。

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