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基于远程实践视频会议平台的声音声学测量的准确性。

Accuracy of Acoustic Measures of Voice via Telepractice Videoconferencing Platforms.

机构信息

Department of Biomedical Engineering, Boston University, MA.

Department of Speech, Language and Hearing Sciences, Boston University, MA.

出版信息

J Speech Lang Hear Res. 2021 Jul 16;64(7):2586-2599. doi: 10.1044/2021_JSLHR-20-00625. Epub 2021 Jun 22.

Abstract

Purpose Telepractice improves patient access to clinical care for voice disorders. Acoustic assessment has the potential to provide critical, objective information during telepractice, yet its validity via telepractice is currently unknown. The current study investigated the accuracy of acoustic measures of voice in a variety of telepractice platforms. Method Twenty-nine voice samples from individuals with dysphonia were transmitted over six video conferencing platforms (Zoom with and without enhancements, Cisco WebEx, Microsoft Teams, Doxy.me, and VSee Messenger). Standard time-, spectral-, and cepstral-based acoustic measures were calculated. The effect of transmission condition on each acoustic measure was assessed using repeated-measures analyses of variance. For those acoustic measures for which transmission condition was a significant factor, linear regression analysis was performed on the difference between the original recording and each telepractice platform, with the overall severity of dysphonia, Internet speed, and ambient noise from the transmitter as predictors. Results Transmission condition was a statistically significant factor for all acoustic measures except for mean fundamental frequency ( ). Ambient noise from the transmitter was a significant predictor of differences between platforms and the original recordings for all acoustic measures except measures. All telepractice platforms affected acoustic measures in a statistically significantly manner, although the effects of platforms varied by measure. Conclusions Overall, measures of were the least impacted by telepractice transmission. Microsoft Teams had the least and Zoom (with enhancements) had the most pronounced effects on acoustic measures. These results provide valuable insight into the relative validity of acoustic measures of voice when collected via telepractice. Supplemental Material https://doi.org/10.23641/asha.14794812.

摘要

目的 远程医疗可改善患者获取语音障碍临床护理的机会。声学评估有可能在远程医疗期间提供关键、客观的信息,但目前尚不清楚其在远程医疗中的有效性。本研究调查了各种远程医疗平台上的语音声学测量的准确性。

方法 将 29 个来自发音障碍者的语音样本通过六种视频会议平台(带和不带增强功能的 Zoom、Cisco WebEx、Microsoft Teams、Doxy.me 和 VSee Messenger)进行传输。计算了基于时间、频谱和倒谱的标准声学测量值。使用重复测量方差分析评估传输条件对每个声学测量值的影响。对于那些传输条件是显著因素的声学测量值,对原始录音和每个远程医疗平台之间的差异进行线性回归分析,以总体嗓音障碍严重程度、互联网速度和发射器环境噪声作为预测因子。

结果 传输条件对所有声学测量值都是一个统计学上显著的因素,除了平均基频( )。发射器的环境噪声是除了 测量值之外,所有声学测量值之间平台和原始录音差异的显著预测因子。除了 测量值外,所有远程医疗平台都以统计学显著的方式影响声学测量值,尽管平台的影响因测量值而异。

结论 总体而言, 测量值受远程医疗传输的影响最小。Microsoft Teams 的影响最小,而 Zoom(带增强功能)对声学测量值的影响最大。这些结果为通过远程医疗采集语音声学测量值的相对有效性提供了有价值的见解。

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Voice Therapy in the Context of the COVID-19 Pandemic: Guidelines for Clinical Practice.
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Variation of the acoustic parameter harmonic-to-noise ratio in relation to different background noise levels.
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3
Acoustic Psychometric Severity Index of Dysphonia (APSID): Development and Clinical Application.
J Voice. 2021 Jul;35(4):660.e19-660.e25. doi: 10.1016/j.jvoice.2019.11.006. Epub 2019 Dec 4.
5
Building a Successful Voice Telepractice Program.
Perspect ASHA Spec Interest Groups. 2019 Feb;4(1):100-110. doi: 10.1044/2018_PERS-SIG3-2018-0014.
6
Assessing voice health using smartphones: bias and random error of acoustic voice parameters captured by different smartphone types.
Int J Lang Commun Disord. 2019 Mar;54(2):292-305. doi: 10.1111/1460-6984.12457. Epub 2019 Feb 19.
7
The relationship between acoustical and perceptual measures of vocal effort.
J Acoust Soc Am. 2018 Sep;144(3):1643. doi: 10.1121/1.5055234.
9
Results of a Survey Offering Clinical Insights into Speech-Language Pathology Telepractice Methods.
Int J Telerehabil. 2017 Nov 20;9(2):25-30. doi: 10.5195/ijt.2017.6230. eCollection 2017 Fall.
10
Maximal Ambient Noise Levels and Type of Voice Material Required for Valid Use of Smartphones in Clinical Voice Research.
J Voice. 2017 Sep;31(5):550-556. doi: 10.1016/j.jvoice.2017.02.017. Epub 2017 Mar 18.

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