Evaluating the Voice Type Component Distributions of Excised Larynx Phonations at Three Subglottal Pressures.
Evaluating the Voice Type Component Distributions of Excised Larynx Phonations at Three Subglottal Pressures.
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DOI：
10.1044/2021_jslhr-20-00429
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发表时间：
2021-04
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通讯作者：
Boquan Liu;Hayley Raj;Logan Klein;Jack J. Jiang
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作者：
Boquan Liu;Hayley Raj;Logan Klein;Jack J. Jiang
目的犬喉切除为研究声音生理学提供了有利的实验框架。近年来，信号处理方法已被应用于犬喉切除实验中的发声分析。然而，语音具有高度的复杂性和非平稳性，对应于规则和混沌信号元素的不同比例。目前用于评估语音不规则程度的非线性动态方法无法识别语音类型分量的分布。方法基于固有维数的测量，提出了一种分析切除喉部实验中发声的VTC分布的方法。对13条切除的犬喉在三种不同声门下压力下的39个发声样本进行了分析。结果声门下压力高于发声不稳定压力（PIP）和低于发声阈值压力（PTP）时产生的发声导致3型和4型声音比例高，其特征是信号混乱和噪声。在PTP和PIP之间通过压力产生的发声以1型语音为主，其特征是信号规律且接近周期性。所有职业训练中心的平均比例，在比较“次PTP”和“PTP”所发出的发音，以及比较“PTP”和“PIP”所发出的发音方面，均有显著差异。结论在所有VTC中，正常和异常语音的VTC分布有显著差异。正常发声与VTC1（声音类型成分1）密切相关，而异常发声则显示VTC4（声音类型成分4）增加。本研究进一步证明了内在维数在声学信号中成功检测多种语音类型的能力，并强调了在人声中扩大使用内在维数的必要性。补充材料https://doi.org/10.23641/asha.14417585。
Purpose The excised canine larynx provides an advantageous experimental framework in the study of voice physiology. In recent years, signal processing methods have been applied to analyze phonations in excised canine larynx experiments. However, phonations have a highly complex and nonstationary nature corresponding to different proportions of regular and chaotic signal elements. Current nonlinear dynamic methods that are used to assess the degree of irregularity in the voice fail to recognize the distribution of voice type components (VTCs). Method Based on measures of intrinsic dimension, this article presents a method to analyze the VTC distribution of phonations in excised canine larynx experiments. Thirty-nine phonation samples from 13 excised canine larynges at three different subglottal pressures were analyzed. Results Phonation produced with subglottal pressures above phonation instability pressure (PIP) and below phonation threshold pressure (PTP) resulted in high proportions of Voice Types 3 and 4, characterized by chaotic and noisy signals. Phonation produced with pressure between PTP and PIP contained mostly Type 1 voice, characterized by a regular and nearly periodic signal. Mean proportions of all VTCs varied significantly in comparisons of phonations produced with Sub-PTP and PTP as well as in comparisons of phonations produced with PTP and PIP. Conclusions Across all VTCs, the VTC profiles of normal and abnormal phonation differ significantly. Normal phonation is strongly associated with VTC1 (Voice Type Component 1), whereas abnormal phonation exhibits increased VTC4 (Voice Type Component 4). The study further demonstrates the ability of intrinsic dimension to successfully detect multiple voice types in an acoustic signal and highlights the need for expanded use of intrinsic dimension in human voice. Supplemental Material https://doi.org/10.23641/asha.14417585.