Acoustic Analysis and Electroglottography in Elite Vocal Performers
Journal of Voice
Background Acoustic analysis of voice (AAV) and electroglottography (EGG) have been used for assessing vocal quality in patients with voice disorders. The effectiveness of these procedures for detecting mild disturbances in vocal quality in elite vocal performers has been controversial. Objective To compare acoustic parameters obtained by AAV and EGG before and after vocal training to determine the effectiveness of these procedures for detecting vocal improvements in elite vocal performers. Materials and Methods Thirty-three elite vocal performers were studied. The study group included 14 males and 19 females, ages 18–40 years, without a history of voice disorders. Acoustic parameters were obtained through AAV and EGG before and after vocal training using the Linklater method. Results Nonsignificant differences (P > 0.05) were found between values of fundamental frequency (F0), shimmer, and jitter obtained by both procedures before vocal training. Mean F0 was similar after vocal training. Jitter percentage as measured by AAV showed nonsignificant differences (P > 0.05) before and after vocal training. Shimmer percentage as measured by AAV demonstrated a significant reduction (P < 0.05) after vocal training. As measured by EGG after vocal training, shimmer and jitter were significantly reduced (P < 0.05); open quotient was significantly increased (P < 0.05); and irregularity was significantly reduced (P < 0.05). Conclusions AAV and EGG were effective for detecting improvements in vocal function after vocal training in male and female elite vocal performers undergoing vocal training. EGG demonstrated better efficacy for detecting improvements and provided additional parameters as compared to AAV.
Villafuerte-Gonzalez R, Valadez-Jimenez VM, Sierra-Ramirez JA, Ysunza PA, Chavarria-Villafuerte K, Hernandez-Lopez X. Acoustic Analysis and Electroglottography in Elite Vocal Performers. J Voice. 2017 May;31(3):391.e1-391.e6. doi: 10.1016/j.jvoice.2016.09.028. Epub 2016 Nov 2. PMID: 27816359.