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Nonlinear dynamical analysis of normal voices

机译:正常声音的非线性动力学分析

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Human voice has been the focus of study for different areas of sciences. Researches in the last two decades have established the existence of chaos in human voice production. The purpose of this paper is to use nonlinear dynamics methods in the analysis of normal voices from healthy subjects and correlate them to traditional acoustic parameters as well as perceptual analysis. Twelve human voice signals from healthy subjects, 6 males and 6 females, ranging in age from 19 to 39 years old were used. Sustained vowel sounds /a/, /e/ and /i/ if, from Brazilian Portuguese were recorded at a sampling rate of 22,050 Hz and analyzed in order to obtain acoustic perturbation measures (jitter, shimmer, coefficient of excess - EX, and pitch amplitude - PA), The phase space reconstruction method was used to describe the nonlinear dynamic characteristics of voice signal samples. This paper shows that nonlinear dynamical methods as phase space reconstruction seems to be a suitable technique for voice signals analysis, due to the chaotic component of the human voice. The results suggest that non-linear dynamic analysis does not replace existing techniques instead they may improve and complement the recent voice analysis methods available for health professionals, speech therapist and clinician.
机译:人类的声音一直是不同科学领域的研究重点。最近二十年来的研究确定了人类声音产生中存在混沌。本文的目的是使用非线性动力学方法来分析来自健康受试者的正常声音,并将其与传统声学参数以及感知分析相关联。使用了来自健康受试者的十二个人类语音信号,分别为19岁至39岁的6名男性和6名女性。以22,050 Hz的采样率记录来自巴西葡萄牙语的持续元音/ a /,/ e /和/ i /,并进行分析,以便获得声学扰动量度(抖动,闪烁,超额系数-EX和音高)振幅-PA),使用相空间重构方法来描述语音信号样本的非线性动态特性。本文表明,由于人类语音的混沌成分,非线性动力学方法作为相空间重构似乎是一种适用于语音信号分析的技术。结果表明,非线性动态分析不能代替现有技术,而是可以改善和补充可供医疗专业人员,言语治疗师和临床医生使用的最新语音分析方法。

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