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用于区分发声障碍严重程度的谐波倒谱声学分析研究

Investigation of the Cepstral Spectral Acoustic Analysis for Classifying the Severity of Dysphonia.

作者信息

İncebay Önal, Köse Ayşen, Esen Aydinli Fatma, Awan Shaheen N, Gürsoy Merve Dilbaz, Yilmaz Taner

机构信息

Department of Speech and Language Therapy, Hacettepe University Faculty of Health Sciences, Sıhhiye, Ankara, Turkey.

Department of Speech and Language Therapy, Hacettepe University Faculty of Health Sciences, Sıhhiye, Ankara, Turkey.

出版信息

J Voice. 2025 May;39(3):844.e19-844.e30. doi: 10.1016/j.jvoice.2022.12.012. Epub 2023 Jan 31.

Abstract

OBJECTIVES

The advantages of cepstral measurements in the evaluation of dysphonia have been noted in previous studies. However, there is an unclarity regarding the results of cepstral analyzes effect in determining the severity of dysphonia. The aims of this study were to determine the cut-off values of cepstral peak prominence, cepstral peak prominence standard deviation, low frequency/ high frequency ratio, low frequency/high frequency ratio standard deviation, and cepstral spectral index of dysphonia for predicting the voice severity within a Turkish speaking population, as well as to confirm the discriminative power of these cut-off values.

MATERIALS METHODS

One hundred ninety-five individuals with voice disorders and an equal number of age and gender-matched individuals without voice disorders were included. Included subjects had visited the Hacettepe University Hospitals Speech and Language Therapy Department for voice evaluation between January 2017 and September 2021. The voice recordings from all participants included the six CAPE-V/Turkish sentences and sustained vowel /a/. Three raters provided auditory perceptual ratings of the voice samples using the GRBAS scale (grade) and overall severity for the CAPE-V/Turkish. Participants were categorized into normal and mild, moderate, and severely dysphonic groups based on the auditory perceptual evaluation. Analysis of Dysphonia in Speech and Voice (ADSV) software was used for cepstral spectral acoustic analysis.

RESULTS

In the sustained vowel context, the area under the curve (ROC) for the CSID value was >0.8, except for mild vs. moderate dysphonia groups. In connected speech contexts, the ROC of the CPP value was also >0.8, except for normal vs. mild dysphonia groups. The cut-off values of CPP and CSID demonstrated high sensitivity and specificity for predicting voice severities.

CONCLUSION

The cut-off values for the parameters that predicted voice severities showed a significant degree of discriminative power for categorizing voice severities among Turkish-speaking people.

摘要

目的

先前的研究已指出倒谱测量在嗓音障碍评估中的优势。然而,关于倒谱分析结果在确定嗓音障碍严重程度方面仍不明确。本研究的目的是确定倒谱峰值突出度、倒谱峰值突出度标准差、低频/高频比值、低频/高频比值标准差以及嗓音障碍的倒谱频谱指数的临界值,以预测土耳其语人群的嗓音严重程度,并确认这些临界值的判别能力。

材料与方法

纳入195名嗓音障碍患者以及同等数量年龄和性别匹配的无嗓音障碍个体。纳入的受试者在2017年1月至2021年9月期间前往哈杰泰佩大学医院言语和语言治疗科进行嗓音评估。所有参与者的嗓音记录包括六个CAPE-V/土耳其语句子和持续元音/a/。三名评估者使用GRBAS量表(等级)和CAPE-V/土耳其语的总体严重程度对嗓音样本进行听觉感知评分。根据听觉感知评估,将参与者分为正常组以及轻度、中度和重度嗓音障碍组。使用语音和嗓音障碍分析(ADSV)软件进行倒谱频谱声学分析。

结果

在持续元音情境下,除轻度与中度嗓音障碍组外,CSID值的曲线下面积(ROC)>0.8。在连贯语音情境下,除正常与轻度嗓音障碍组外,CPP值的ROC也>0.8。CPP和CSID的临界值在预测嗓音严重程度方面表现出高敏感性和特异性。

结论

预测嗓音严重程度的参数临界值在对土耳其语人群的嗓音严重程度进行分类时显示出显著的判别能力。

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