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本文引用的文献

1
Accuracy of Acoustic Measures of Voice via Telepractice Videoconferencing Platforms.基于远程实践视频会议平台的声音声学测量的准确性。
J Speech Lang Hear Res. 2021 Jul 16;64(7):2586-2599. doi: 10.1044/2021_JSLHR-20-00625. Epub 2021 Jun 22.
2
The Effects of Speech Compression Algorithms on the Intelligibility of Two Individuals With Dysarthric Speech.语音压缩算法对两位构音障碍者言语清晰度的影响。
Am J Speech Lang Pathol. 2019 Feb 21;28(1):195-203. doi: 10.1044/2018_AJSLP-18-0081.
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Characterizing the distribution of the quadrilateral vowel space area.描绘四边形元音空间区域的分布情况。
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Automatic assessment of vowel space area.自动评估元音空间面积。
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Treating disordered speech and voice in Parkinson's disease online: a randomized controlled non-inferiority trial.在线治疗帕金森病患者的言语和嗓音障碍:一项随机对照非劣效性试验。
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The redesign and re-evaluation of an internet-based telerehabilitation system for the assessment of dysarthria in adults.重新设计和重新评估基于互联网的远程康复系统,以评估成人的构音障碍。
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研究语音压缩对构音障碍语音声学特征的影响。

Investigating the Impact of Speech Compression on the Acoustics of Dysarthric Speech.

作者信息

Tran Kelvin, Xu Lingfeng, Stegmann Gabriela, Liss Julie, Berisha Visar, Utianski Rene L

机构信息

Arizona State University, USA.

Aural Analytics, USA.

出版信息

Interspeech. 2022 Sep;2022:2263-2267. doi: 10.21437/interspeech.2022-10817.

DOI:10.21437/interspeech.2022-10817
PMID:39493500
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC11529786/
Abstract

Acoustic analysis plays an important role in the assessment of dysarthria. Out of a public health necessity, telepractice has become increasingly adopted as the modality in which clinical care is given. While there are differences in software among telepractice platforms, they all use some form of speech compression to preserve bandwidth, with the most common algorithm being the Opus codec. Opus has been optimized for compression of speech from the general (mostly healthy) population. As a result, for speech-language pathologists, this begs the question: is the remotely transmitted speech signal a faithful representation of dysarthric speech? Existing high-fidelity audio recordings from 20 speakers of various dysarthria types were encoded at three different bit rates defined within Opus to simulate different internet bandwidth conditions. Acoustic measures of articulation, voice, and prosody were extracted, and mixed-effect models were used to evaluate the impact of bandwidth conditions on the measures. Significant differences in cepstral peak prominence, degree of voice breaks, jitter, vowel space area, pitch, and vowel space area were observed after Opus processing, providing insight into the types of acoustic measures that are susceptible to speech compression algorithms.

摘要

声学分析在构音障碍评估中起着重要作用。出于公共卫生需求,远程医疗已越来越多地被用作提供临床护理的方式。虽然远程医疗平台之间的软件存在差异,但它们都使用某种形式的语音压缩来节省带宽,最常用的算法是Opus编解码器。Opus已针对一般(大多为健康)人群的语音压缩进行了优化。因此,对于言语治疗师来说,这就引出了一个问题:远程传输的语音信号是否能如实反映构音障碍语音?从20名不同类型构音障碍患者那里获取的现有高保真音频记录,按照Opus中定义的三种不同比特率进行编码,以模拟不同的网络带宽条件。提取了清晰度、嗓音和韵律方面的声学指标,并使用混合效应模型来评估带宽条件对这些指标的影响。经过Opus处理后,观察到谐波峰值突出度、嗓音中断程度、抖动、元音空间面积、音高和谐波峰值突出度等方面存在显著差异,这为了解易受语音压缩算法影响的声学指标类型提供了依据。