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Fatigue estimation using voice analysis

机译:使用语音分析进行疲劳评估

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摘要

In the present article, we present a means to remotely and transparently estimate an individual’s level of fatigue by quantifying changes in his or her voice characteristics. Using Voice analysis to estimate fatigue is unique from established cognitive measures in a number of ways: (1) speaking is a natural activity requiring no initial training or learning curve, (2) voice recording is a unobtrusive operation allowing the speakers to go about their normal work activities, (3) using telecommunication infrastructure (radio, telephone, etc.) a diffuse set of remote populations can be monitored at a central location, and (4) often, previously recorded voice data are available for post hoc analysis. By quantifying changes in the mathematical coefficients that describe the human speech production process, we were able to demonstrate that for speech sounds requiring a large average air flow, a speaker’s voice changes in synchrony with both direct measures of fatigue and with changes predicted by the length of time awake.
机译:在本文中,我们提出了一种通过量化个人语音特征的变化来远程透明地估计其疲劳程度的方法。使用语音分析来估计疲劳在许多方面是已建立的认知测量方法所独有的:(1)说话是一种自然活动,不需要初始训练或学习曲线;(2)录音是一项不引人注目的操作,使说话者可以自行处理正常的工作活动;(3)使用电信基础结构(无线电,电话等),可以在中央位置监视一组分散的偏远人口;(4)通常,以前录制的语音数据可用于事后分析。通过量化描述人类语音产生过程的数学系数的变化,我们能够证明,对于需要大量平均气流的语音,说话人的声音变化与疲劳的直接量度和长度预测的变化同步时间清醒。

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