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使用VOXplot进行临床嗓音质量分析的进展

Advances in Clinical Voice Quality Analysis with VOXplot.

作者信息

Barsties V Latoszek Ben, Mayer Jörg, Watts Christopher R, Lehnert Bernhard

机构信息

Speech-Language Pathology, SRH University of Applied Health Sciences, 40210 Düsseldorf, Germany.

Institute for Natural Language Processing, University of Stuttgart, 70049 Stuttgart, Germany.

出版信息

J Clin Med. 2023 Jul 12;12(14):4644. doi: 10.3390/jcm12144644.

Abstract

BACKGROUND

The assessment of voice quality can be evaluated perceptually with standard clinical practice, also including acoustic evaluation of digital voice recordings to validate and further interpret perceptual judgments. The goal of the present study was to determine the strongest acoustic voice quality parameters for perceived hoarseness and breathiness when analyzing the sustained vowel [a:] using a new clinical acoustic tool, the VOXplot software.

METHODS

A total of 218 voice samples of individuals with and without voice disorders were applied to perceptual and acoustic analyses. Overall, 13 single acoustic parameters were included to determine validity aspects in relation to perceptions of hoarseness and breathiness.

RESULTS

Four single acoustic measures could be clearly associated with perceptions of hoarseness or breathiness. For hoarseness, the harmonics-to-noise ratio (HNR) and pitch perturbation quotient with a smoothing factor of five periods (PPQ5), and, for breathiness, the smoothed cepstral peak prominence (CPPS) and the glottal-to-noise excitation ratio (GNE) were shown to be highly valid, with a significant difference being demonstrated for each of the other perceptual voice quality aspects.

CONCLUSIONS

Two acoustic measures, the HNR and the PPQ5, were both strongly associated with perceptions of hoarseness and were able to discriminate hoarseness from breathiness with good confidence. Two other acoustic measures, the CPPS and the GNE, were both strongly associated with perceptions of breathiness and were able to discriminate breathiness from hoarseness with good confidence.

摘要

背景

嗓音质量的评估可以通过标准临床实践进行感知评估,也包括对数字语音记录进行声学评估,以验证并进一步解释感知判断。本研究的目的是使用一种新的临床声学工具VOXplot软件,在分析持续元音[a:]时,确定与感知到的嘶哑和呼吸音相关的最强声学嗓音质量参数。

方法

对218份有或无嗓音障碍个体的嗓音样本进行感知和声学分析。总共纳入了13个单一声学参数,以确定与嘶哑和呼吸音感知相关的有效性方面。

结果

四项单一声学测量与嘶哑或呼吸音的感知有明显关联。对于嘶哑,谐波噪声比(HNR)和平滑因子为五个周期的音高微扰商(PPQ5),对于呼吸音,平滑的谐波峰值突出度(CPPS)和声门噪声激励比(GNE)被证明具有高度有效性,在其他每个感知嗓音质量方面都显示出显著差异。

结论

两项声学测量,即HNR和PPQ5,都与嘶哑的感知密切相关,并且能够很有把握地将嘶哑与呼吸音区分开来。另外两项声学测量,即CPPS和GNE,都与呼吸音的感知密切相关,并且能够很有把握地将呼吸音与嘶哑区分开来。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/6086/10380658/90a9509ef130/jcm-12-04644-g001.jpg

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