The Influence of Voice Training on Vocal Learner's Objective Acoustic Voice Components

Wu, Pinhong; Klein, Logan; Rozema, Z; Haderlein, Nicole; Cai, Jie; Scholp, Austin; Xu, Xiufeng; Jiang, Jack J.; Zhuang, Pinghui

doi:10.1016/j.jvoice.2021.01.011

Cited by 4 publications

(1 citation statement)

References 25 publications

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“…Wuyts et al’s DSI model, presented in 2000, is a multivariate model that provides an objective and quantitative indicator of overall voice quality by incorporating acoustic (jitter, and the lowest intensity and highest fundamental frequency in the vocal range profile) and aerodynamic (maximum phonation time of the vowel [a:]) markers [ 9 ]. DSI has been regarded as a valuable and viable assessment for assessing overall voice quality, voice treatment, vocal training, and phonosurgery results [ 10 , 11 , 12 , 13 , 14 , 15 , 16 , 17 ]. Additional research found connections between the DSI and auditory-perceptual judgment and quality of life evaluation, establishing the DSI as a valid approach for evaluating dysphonia severity [ 13 , 14 , 15 , 18 , 19 , 20 ].…”

Section: Introductionmentioning

confidence: 99%

Accuracy Analysis of the Multiparametric Acoustic Voice Indices, the VWI, AVQI, ABI, and DSI Measures, in Differentiating between Normal and Dysphonic Voices

Uloza,

Pribuišis,

Ulozaite-Staniene

et al. 2023

JCM

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The study aimed to investigate and compare the accuracy and robustness of the multiparametric acoustic voice indices (MAVIs), namely the Dysphonia Severity Index (DSI), Acoustic Voice Quality Index (AVQI), Acoustic Breathiness Index (ABI), and Voice Wellness Index (VWI) measures in differentiating normal and dysphonic voices. The study group consisted of 129 adult individuals including 49 with normal voices and 80 patients with pathological voices. The diagnostic accuracy of the investigated MAVI in differentiating between normal and pathological voices was assessed using receiver operating characteristics (ROC). Moderate to strong positive linear correlations were observed between different MAVIs. The ROC statistical analysis revealed that all used measurements manifested in a high level of accuracy (area under the curve (AUC) of 0.80 and greater) and an acceptable level of sensitivity and specificity in discriminating between normal and pathological voices. However, with AUC 0.99, the VWI demonstrated the highest diagnostic accuracy. The highest Youden index equaled 0.93, revealing that a VWI cut-off of 4.45 corresponds with highly acceptable sensitivity (97.50%) and specificity (95.92%). In conclusion, the VWI was found to be beneficial in describing differences in voice quality status and discriminating between normal and dysphonic voices based on clinical diagnosis, i.e., dysphonia type, implying the VWI’s reliable voice screening potential.

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