VTC distribution at three subglottal pressures (Liu et al., 2021)

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 S1. Voice type component profile for phonation under phonation threshold pressure (PTP; see Figure 5). Voice type component profile for normal phonation (120% PTP). PTP = phonation threshold pressure (see Figure 6).Voice type component profile for phonation over PIP (150% PIP). PIP = phonation instability pressure (see Figure 7). Liu, B., Raj, H., Klein, L., & Jiang, J. J. (2021). Evaluating the voice type component distributions of excised larynx phonations at three subglottal pressures. Journal of Speech, Language, and Hearing Research. Advance online publication. https://doi.org/10.1044/2021_JSLHR-20-00429

目的：切除的犬类喉头构成了研究声音生理学的有利实验框架。近年来，信号处理方法已应用于分析切除犬类喉头实验中的发音。然而，发音具有高度复杂且非平稳的本质，对应着不同比例的规则与混沌信号元素。目前用于评估声音不规则程度的非线性动态方法，未能识别声音类型成分（VTCs）的分布。方法：基于内在维度的度量，本文提出了一种分析切除犬类喉头实验中发音VTC分布的方法。对13个切除犬喉在不同亚声门压力下的39个发音样本进行了分析。结果：在发音不稳定压力（PIP）之上、发音阈值压力（PTP）之下的亚声门压力产生的发音，导致声音类型3和4的比例较高，其特征为混沌和噪声信号。在PTP与PIP之间的压力产生的发音，主要包含类型1的声音，其特征为规则且近乎周期性的信号。所有VTCs的平均比例在亚PTP与PTP产生的发音之间的比较，以及在PTP与PIP产生的发音之间的比较中均存在显著差异。结论：在所有VTCs中，正常与异常发音的VTC轮廓存在显著差异。正常发音与VTC1（声音类型成分1）密切相关，而异常发音表现出VTC4（声音类型成分4）的增加。该研究进一步证明了内在维度在成功检测声学信号中的多种声音类型方面的能力，并强调了在人类声音中扩展使用内在维度的必要性。补充材料S1：发音阈值压力（PTP，见图5）下的声音类型成分轮廓。正常发音的声音类型成分轮廓（120% PTP）。PTP = 发音阈值压力（见图6）。超过发音不稳定压力（PIP）的发音的声音类型成分轮廓（150% PIP）。PIP = 发音不稳定压力（见图7）。刘波，拉吉，克莱因，及姜建杰。（2021）。在三个亚声门压力下评估切除喉头发音的声音类型成分分布。言语、语言和听力研究杂志。在线提前发表。https://doi.org/10.1044/2021_JSLHR-20-00429