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基于语音包络神经同步预测语音可懂度。

Speech Intelligibility Predicted from Neural Entrainment of the Speech Envelope.

作者信息

Vanthornhout Jonas, Decruy Lien, Wouters Jan, Simon Jonathan Z, Francart Tom

机构信息

Department of Neurosciences, ExpORL, KU Leuven - University of Leuven, Leuven, Belgium.

Department of Electrical and Computer Engineering, University of Maryland, College Park, MD, USA.

出版信息

J Assoc Res Otolaryngol. 2018 Apr;19(2):181-191. doi: 10.1007/s10162-018-0654-z. Epub 2018 Feb 20.

Abstract

Speech intelligibility is currently measured by scoring how well a person can identify a speech signal. The results of such behavioral measures reflect neural processing of the speech signal, but are also influenced by language processing, motivation, and memory. Very often, electrophysiological measures of hearing give insight in the neural processing of sound. However, in most methods, non-speech stimuli are used, making it hard to relate the results to behavioral measures of speech intelligibility. The use of natural running speech as a stimulus in electrophysiological measures of hearing is a paradigm shift which allows to bridge the gap between behavioral and electrophysiological measures. Here, by decoding the speech envelope from the electroencephalogram, and correlating it with the stimulus envelope, we demonstrate an electrophysiological measure of neural processing of running speech. We show that behaviorally measured speech intelligibility is strongly correlated with our electrophysiological measure. Our results pave the way towards an objective and automatic way of assessing neural processing of speech presented through auditory prostheses, reducing confounds such as attention and cognitive capabilities. We anticipate that our electrophysiological measure will allow better differential diagnosis of the auditory system, and will allow the development of closed-loop auditory prostheses that automatically adapt to individual users.

摘要

目前,言语可懂度是通过对一个人识别语音信号的能力进行评分来衡量的。此类行为测量的结果反映了语音信号的神经处理过程,但也受到语言处理、动机和记忆的影响。通常,听力的电生理测量能够洞察声音的神经处理过程。然而,在大多数方法中,使用的是非语音刺激,这使得很难将结果与言语可懂度的行为测量联系起来。在听力的电生理测量中使用自然流畅的语音作为刺激是一种范式转变,它能够弥合行为测量和电生理测量之间的差距。在此,通过从脑电图中解码语音包络,并将其与刺激包络相关联,我们展示了一种对流畅语音神经处理的电生理测量方法。我们表明,行为测量的言语可懂度与我们的电生理测量密切相关。我们的研究结果为通过听觉假体呈现的语音神经处理评估提供了一种客观、自动的方法,减少了诸如注意力和认知能力等混淆因素。我们预计,我们的电生理测量将有助于对听觉系统进行更好的鉴别诊断,并将推动自动适应个体用户的闭环听觉假体的开发。

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