Voice disorder discrimination using vowel acoustic measures in female speakers

IF 1.5 3区医学 Q2 AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY

International Journal of Language & Communication Disorders Pub Date : 2024-06-17 DOI:10.1111/1460-6984.13081

Duy Duong Nguyen, Daniel Novakovic, Catherine Madill

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To date, no study has combined vowel acoustic measures only that evaluate major aspects of the pathological voice signals in voice disorder discrimination.</p>\n </section>\n \n <section>\n \n <h3> Aims</h3>\n \n <p>To investigate the value of vowel acoustic measures that quantify glottal noise, signal stability, signal periodicity, spectral slope and overall voice quality in discriminating female speakers with and without voice disorders.</p>\n </section>\n \n <section>\n \n <h3> Methods & Procedures</h3>\n \n <p>Sustained vowel /ɑ/ samples were extracted from 133 voice-disordered female patients and 97 non-voice disordered female speakers and were signal typed prior to analysis. <i>Praat</i> software was used to measure harmonics-to-noise ratio (HNR), glottal-to-noise excitation ratio (GNE), the standard deviation of fundamental frequency (F0SD) and cepstral peak prominence (CPPp); and the <i>Analysis of Dysphonia in Speech and Voice</i> (ADSV) program was used to measure CPPadsv, low/high spectral ratio (LH) and the cepstral/spectral index of dysphonia (CSID). 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引用次数: 0

Abstract

Background

Sustained vowels are important vocal tasks that have been investigated in discriminating voice disorders using acoustic analysis. To date, no study has combined vowel acoustic measures only that evaluate major aspects of the pathological voice signals in voice disorder discrimination.

Aims

To investigate the value of vowel acoustic measures that quantify glottal noise, signal stability, signal periodicity, spectral slope and overall voice quality in discriminating female speakers with and without voice disorders.

Methods & Procedures

Sustained vowel /ɑ/ samples were extracted from 133 voice-disordered female patients and 97 non-voice disordered female speakers and were signal typed prior to analysis. Praat software was used to measure harmonics-to-noise ratio (HNR), glottal-to-noise excitation ratio (GNE), the standard deviation of fundamental frequency (F0SD) and cepstral peak prominence (CPPp); and the Analysis of Dysphonia in Speech and Voice (ADSV) program was used to measure CPPadsv, low/high spectral ratio (LH) and the cepstral/spectral index of dysphonia (CSID). Outcome measures included sensitivity, specificity, and discrimination accuracy.

Outcomes & Results

As individual acoustic measures, only spectral-based measures showed good (CPPadsv) and acceptable (CSID) discrimination results. The HNR, GNE and CPPp measures had acceptable sensitivity but poor or non-acceptable specificity and discrimination accuracy. Logistic regression models with all Praat measures (F0SD, HNR, GNE, CPPp) plus ADSV measures (CPPadsv, LH or CSID) provided excellent sensitivity, good-to-excellent specificity and excellent discrimination accuracy. ROC analysis for all individual measures showed that CPPadsv, CSID, CPPp, GNE and F0SD had the highest area under the curve (AUC) values.

Conclusions & Implications

A combination of acoustic measures that evaluate the major aspects of vocal dysfunction resulted in good to excellent voice discrimination outcomes. Individual acoustic measures had lower discrimination ability than combined measures. The findings implied that acoustic measures extracted from a prolonged vowel were useful in voice disorder discrimination.

WHAT THIS PAPER ADDS

What is already known on this subject

Acoustic measures hold great value in discriminating voice disorders from normal voices. However, no study has evaluated discrimination values of a combination of sustained vowel acoustic measures that quantify additive noise, signal stability, signal periodicity, spectral slope and overall voice quality in single-gender cohorts. Previous studies have not used signal typing (the classification of the acoustic signals) for time-based measures, impacting the reliability of discrimination.

What this study adds to the existing knowledge

This study was the first to implement signal typing to include sustained vowel samples of Types 1 and 2 signals for discrimination statistics. We showed that a combination of vocal acoustic measures using time- and spectral-based extraction from the sustained /ɑ/ vowel evaluating additive noise, signal stability, signal periodicity, spectral slope and overall voice quality resulted in good to excellent sensitivity, specificity and discrimination accuracy. As individual measures, traditional time-based measures such as HNR had rather limited discrimination values whilst spectral-based measures provided higher discrimination values. Measures that are sensitive to signal types have low discrimination ability.

What are the potential or actual clinical implications of this work?

The sustained vowel /ɑ/ is a relevant, universal vocal task for clinical application using acoustic measures to discriminate female speakers with and without voice disorders if signal typing is implemented. Clinical voice assessment using vowels may not be effective if relying solely on time-based measurements. Spectral-based measures perform better in voice disorder discrimination given their insensitivity to signal types. The most effective voice disorder discrimination could only be obtained using a combination of acoustic measures that quantify major phenomena in the signals of disordered voices. Using measures extracted from both programs, Praat and ADSV, is useful given that specific settings in a program may impact on discrimination accuracy.

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利用元音声学测量方法辨别女性说话者的语音失常。

背景：持续元音是一项重要的发声任务，在利用声学分析鉴别嗓音疾病时已对其进行了研究。目的：研究量化声门噪声、信号稳定性、信号周期性、频谱斜率和整体语音质量的元音声学测量方法在鉴别有无嗓音障碍的女性说话者中的价值：从 133 名嗓音障碍女性患者和 97 名非嗓音障碍女性说话者中提取持续元音 /ɑ/ 样本，并在分析前进行信号分型。Praat 软件用于测量谐波噪声比 (HNR)、声门噪声激励比 (GNE)、基频标准偏差 (F0SD) 和epstral 峰值突出 (CPPp)；语音和嗓音发音障碍分析 (ADSV) 程序用于测量 CPPadsv、低/高频谱比 (LH) 和发音障碍epstral/spectral 指数 (CSID)。结果测量包括灵敏度、特异性和辨别准确性：作为单独的声学测量方法，只有基于频谱的测量方法显示出良好（CPPadsv）和可接受（CSID）的辨别结果。HNR、GNE 和 CPPp 的灵敏度可接受，但特异性和辨别准确性较差或不可接受。使用所有 Praat 测量（F0SD、HNR、GNE、CPPp）和 ADSV 测量（CPPadsv、LH 或 CSID）的逻辑回归模型提供了极好的灵敏度、极好到极好的特异性和极好的辨别准确性。对所有单项测量的 ROC 分析表明，CPPadsv、CSID、CPPp、GNE 和 F0SD 的曲线下面积（AUC）值最高：结论与启示：综合评估发声功能障碍主要方面的声学测量结果可获得良好至卓越的嗓音辨别结果。单个声学指标的辨别能力低于综合指标。研究结果表明，从延长元音中提取的声学测量方法有助于辨别嗓音障碍：对这一问题的认识声学测量在鉴别嗓音失调和正常嗓音方面具有重要价值。然而，目前还没有研究对持续元音声学测量组合的鉴别值进行评估，这些测量组合可量化单性别群体中的加性噪声、信号稳定性、信号周期性、频谱斜率和整体嗓音质量。以前的研究没有对基于时间的测量进行信号分型（声学信号的分类），这影响了辨别的可靠性。本研究对现有知识的补充本研究首次采用信号分型，将 1 类和 2 类信号的持续元音样本纳入辨别统计。我们的研究表明，将基于时间和频谱的持续元音/ɑ/提取方法与评估加性噪声、信号稳定性、信号周期性、频谱斜率和整体语音质量的声学测量方法相结合，可获得良好至卓越的灵敏度、特异性和判别准确性。作为单独的测量方法，传统的基于时间的测量方法（如 HNR）的判别值相当有限，而基于频谱的测量方法则能提供较高的判别值。对信号类型敏感的测量方法辨别能力较低。这项研究的潜在或实际临床意义是什么？持续元音/ɑ/是一项相关的通用发声任务，在临床应用中，如果采用信号分型法，可使用声学测量方法来区分有无嗓音障碍的女性说话者。如果仅依靠基于时间的测量方法，使用元音进行临床嗓音评估可能效果不佳。基于频谱的测量方法对信号类型不敏感，因此在鉴别嗓音失常方面表现更好。只有将能量化失常嗓音信号中主要现象的声学测量方法结合起来，才能获得最有效的嗓音失常判别方法。使用从 Praat 和 ADSV 两个程序中提取的测量值非常有用，因为程序中的特定设置可能会影响辨别准确性。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

International Journal of Language & Communication Disorders AUDIOLOGY & SPEECH-LANGUAGE PATHOLOGY-REHABILITATION

CiteScore

3.30

自引率

12.50%

发文量

116

审稿时长

6-12 weeks

期刊介绍： The International Journal of Language & Communication Disorders (IJLCD) is the official journal of the Royal College of Speech & Language Therapists. The Journal welcomes submissions on all aspects of speech, language, communication disorders and speech and language therapy. It provides a forum for the exchange of information and discussion of issues of clinical or theoretical relevance in the above areas.