Ben Barsties V Latoszek1, Youri Maryn2, Ellen Gerrits3, Marc De Bodt4. 1. Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Institute of Health Studies, HAN University of Applied Sciences, Nijmegen, The Netherlands. Electronic address: ben.barsties@t-online.de. 2. Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; European Institute for ORL, Sint-Augustinus Hospital, Antwerp, Belgium; Faculty of Education, Health & Social Work, University College Ghent, Ghent, Belgium. 3. Faculty of Health Care, HU University of Applied Sciences Utrecht, Utrecht, The Netherlands; Faculty of Humanities, University of Utrecht, Utrecht, The Netherlands; Department of Otolaryngology, University Medical Center Utrecht, Utrecht, The Netherlands. 4. Faculty of Medicine and Health Sciences, University of Antwerp, Antwerp, Belgium; Department of Otorhinolaryngology and Head & Neck Surgery, Antwerp University Hospital, Antwerp, Belgium; Faculty of Medicine & Health Sciences, University of Ghent, Ghent, Belgium.
Abstract
OBJECTIVE: The evaluation of voice quality is a major component of voice assessment. The aim of the present study was to develop a new multivariate acoustic model for the evaluation of breathiness. METHOD: Concatenated voice samples of continuous speech and the sustained vowel [a:] from 970 subjects with dysphonia and 88 vocally healthy subjects were perceptually judged for breathiness severity. Acoustic analyses were conducted on the same concatenated voice samples after removal of the non-voiced segments of the continuous speech sample. The development of an acoustic model for breathiness was based on stepwise multiple linear regression analysis. Concurrent validity, diagnostic accuracy, and cross validation were statistically verified on the basis of the Spearman rank-order correlation coefficient (rs), several estimates of the receiver operating characteristics plus the likelihood ratio, and iterated internal cross correlations. RESULTS: Ratings of breathiness from four experts with moderate reliability were used. Stepwise multiple regression analysis yielded a nine-variable acoustic model for the multiparametric measurement of breathiness (Acoustic Breathiness Index [ABI]). A strong correlation was found between ABI and auditory-perceptual rating (rs = 0.840, P = 0.000). The cross correlations confirmed a comparably high degree of association. Additionally, the receiver operating characteristics and likelihood ratio results showed the best diagnostic outcome at a threshold of ABI = 3.44 with a sensitivity of 82.4% and a specificity of 92.9%. CONCLUSIONS: This study developed a new acoustic multivariate correlate for the evaluation of breathiness in voice. The ABI model showed valid and robust results and is therefore proposed as a new acoustic index for the evaluation of breathiness.
OBJECTIVE: The evaluation of voice quality is a major component of voice assessment. The aim of the present study was to develop a new multivariate acoustic model for the evaluation of breathiness. METHOD: Concatenated voice samples of continuous speech and the sustained vowel [a:] from 970 subjects with dysphonia and 88 vocally healthy subjects were perceptually judged for breathiness severity. Acoustic analyses were conducted on the same concatenated voice samples after removal of the non-voiced segments of the continuous speech sample. The development of an acoustic model for breathiness was based on stepwise multiple linear regression analysis. Concurrent validity, diagnostic accuracy, and cross validation were statistically verified on the basis of the Spearman rank-order correlation coefficient (rs), several estimates of the receiver operating characteristics plus the likelihood ratio, and iterated internal cross correlations. RESULTS: Ratings of breathiness from four experts with moderate reliability were used. Stepwise multiple regression analysis yielded a nine-variable acoustic model for the multiparametric measurement of breathiness (Acoustic Breathiness Index [ABI]). A strong correlation was found between ABI and auditory-perceptual rating (rs = 0.840, P = 0.000). The cross correlations confirmed a comparably high degree of association. Additionally, the receiver operating characteristics and likelihood ratio results showed the best diagnostic outcome at a threshold of ABI = 3.44 with a sensitivity of 82.4% and a specificity of 92.9%. CONCLUSIONS: This study developed a new acoustic multivariate correlate for the evaluation of breathiness in voice. The ABI model showed valid and robust results and is therefore proposed as a new acoustic index for the evaluation of breathiness.
Authors: Elizabeth S Heller Murray; Carolyn M Michener; Laura Enflo; Gabriel J Cler; Cara E Stepp Journal: J Voice Date: 2017-08-31 Impact factor: 2.009
Authors: Mara R Kapsner-Smith; Manuel E Díaz-Cádiz; Jennifer M Vojtech; Daniel P Buckley; Daryush D Mehta; Robert E Hillman; Lauren F Tracy; J Pieter Noordzij; Tanya L Eadie; Cara E Stepp Journal: J Speech Lang Hear Res Date: 2022-03-10 Impact factor: 2.674