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人类听觉皮层中语音信息处理的分段窗口。

Segmentation window of speech information processing in the human auditory cortex.

机构信息

Department of Interdisciplinary Science and Engineering, School of Science and Engineering, Meisei University, Tokyo, 191-8506, Japan.

Department of Functioning and Disability, Institute for Developmental Research, Aichi Developmental Disability Center, Kasugai, Japan.

出版信息

Sci Rep. 2024 Oct 24;14(1):25044. doi: 10.1038/s41598-024-76137-y.

Abstract

Humans perceive continuous speech signals as discrete sequences. To clarify the temporal segmentation window of speech information processing in the human auditory cortex, the relationship between speech perception and cortical responses was investigated using auditory evoked magnetic fields (AEFs). AEFs were measured while participants heard synthetic Japanese words /atataka/. There were eight types of /atataka/ with different speech rates. The durations of the words ranged from 75 to 600 ms. The results revealed a clear correlation between the AEFs and syllables. Specifically, when the durations of the words were between 375 and 600 ms, the evoked responses exhibited four clear responses from the superior temporal area, M100, that corresponded not only to the onset of speech but also to each group of consonant/vowel syllable units. The number of evoked M100 responses was correlated to the duration of the stimulus as well as the number of perceived syllables. The approximate range of the temporal segmentation window limit of speech perception was considered to be between 75 and 94 ms. This finding may contribute to optimizing the temporal performance of high-speed synthesized speech generation systems.

摘要

人类将连续的语音信号感知为离散的序列。为了阐明人类听觉皮层中语音信息处理的时间分割窗口,使用听觉诱发磁场 (AEF) 研究了语音感知与皮质反应之间的关系。当参与者听到合成的日语单词 /atataka/ 时,测量了 AEF。/atataka/ 有八种类型,语速不同。单词的持续时间从 75 毫秒到 600 毫秒不等。结果表明 AEF 与音节之间存在明显的相关性。具体来说,当单词的持续时间在 375 到 600 毫秒之间时,诱发反应从颞上区显示出四个清晰的响应 M100,这些响应不仅对应于语音的起始,还对应于每个辅音/元音音节单元组。诱发的 M100 响应的数量与刺激的持续时间以及感知到的音节数量相关。语音感知的时间分割窗口限制的大致范围被认为在 75 到 94 毫秒之间。这一发现可能有助于优化高速合成语音生成系统的时间性能。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc8f/11502806/7c497cd5a0dd/41598_2024_76137_Fig1_HTML.jpg

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