Lee Yeon Woo, Kim Geun Hyo
Department of Speech-Language Pathology, Kosin University, Busan, Republic of Korea.
Department of Otorhinolaryngology-Head and Neck Surgery and Biomedical Research Institute, Pusan National University Hospital, Busan, Republic of Korea.
J Voice. 2024 Aug 22. doi: 10.1016/j.jvoice.2024.07.014.
The purposes of this study were (1) to analyze the reliability of direct magnitude estimation (DME) in auditory perceptual assessments measuring dysphonia severity and (2) to analyze the relationship between DME and four acoustic parameters (cepstral peak prominence [CPP], cepstral peak prominence-smoothed [CPPs], Acoustic Voice Quality Index [AVQI], and Acoustic Breathiness Index [ABI]) and (3) to predict dysphonia severity based on DME using four acoustic parameters.
One hundred and sixty-one voice samples for dysphonia patients were used. In this study, we combined sustained vowel samples and connected speech samples using the Praat software to make the concatenated samples for implementing acoustic analysis and auditory perceptual assessments. For acoustic analysis, we analyzed each value of CPP, CPPs, AVQI, and ABI. For auditory perceptual assessments, three speech-language pathologists evaluated dysphonia severity from the concatenated samples. Finally, we performed a stepwise multiple regression analysis to verify which combination of the four acoustic parameters could best predict perceived dysphonia severity based on the DME.
DME was found to have high reliability for auditory perceptual assessments measuring dysphonia severity, and there was a significant correlation between DME and four acoustic parameters. Finally, a two-variable model (AVQI and ABI) was useful for predicting perceived dysphonia severity based on the DME.
We verified the usefulness of DME scales in judging the dysphonia severity of dysphonic patients when used with acoustic analysis. Also, the two-variable model was useful to predict perceived dysphonia severity based on the DME.
本研究的目的是：（1）分析直接量级估计法（DME）在测量发声障碍严重程度的听觉感知评估中的可靠性；（2）分析DME与四个声学参数（谐波峰值突出度[CPP]、平滑谐波峰值突出度[CPPs]、声学嗓音质量指数[AVQI]和声学呼吸音指数[ABI]）之间的关系；（3）使用四个声学参数，基于DME预测发声障碍严重程度。
使用了161份发声障碍患者的语音样本。在本研究中，我们使用Praat软件将持续元音样本和连贯语音样本合并，以制作用于进行声学分析和听觉感知评估的拼接样本。对于声学分析，我们分析了CPP、CPPs、AVQI和ABI的每个值。对于听觉感知评估，三名言语病理学家从拼接样本中评估发声障碍严重程度。最后，我们进行了逐步多元回归分析，以验证四个声学参数的哪种组合能够基于DME最好地预测感知到的发声障碍严重程度。
发现DME在测量发声障碍严重程度的听觉感知评估中具有高可靠性，并且DME与四个声学参数之间存在显著相关性。最后，一个双变量模型（AVQI和ABI）对于基于DME预测感知到的发声障碍严重程度是有用的。
我们验证了DME量表在与声学分析一起使用时，对于判断发声障碍患者发声障碍严重程度的有用性。此外，双变量模型对于基于DME预测感知到的发声障碍严重程度是有用的。
