caa a22 4500 60618757X CHVBK 20210128100841.0 cr unu---uuuuu 210128e20151101xx s 000 0 eng 10.1007/s00405-015-3708-4 doi (NATIONALLICENCE)springer-10.1007/s00405-015-3708-4 Exploring the feasibility of smart phone microphone for measurement of acoustic voice parameters and voice pathology screening [Elektronische Daten] [Virgilijus Uloza, Evaldas Padervinskis, Aurelija Vegiene, Ruta Pribuisiene, Viktoras Saferis, Evaldas Vaiciukynas, Adas Gelzinis, Antanas Verikas] The objective of this study is to evaluate the reliability of acoustic voice parameters obtained using smart phone (SP) microphones and investigate the utility of use of SP voice recordings for voice screening. Voice samples of sustained vowel/a/obtained from 118 subjects (34 normal and 84 pathological voices) were recorded simultaneously through two microphones: oral AKG Perception 220 microphone and SP Samsung Galaxy Note3 microphone. Acoustic voice signal data were measured for fundamental frequency, jitter and shimmer, normalized noise energy (NNE), signal to noise ratio and harmonic to noise ratio using Dr. Speech software. Discriminant analysis-based Correct Classification Rate (CCR) and Random Forest Classifier (RFC) based Equal Error Rate (EER) were used to evaluate the feasibility of acoustic voice parameters classifying normal and pathological voice classes. Lithuanian version of Glottal Function Index (LT_GFI) questionnaire was utilized for self-assessment of the severity of voice disorder. The correlations of acoustic voice parameters obtained with two types of microphones were statistically significant and strong (r=0.73-1.0) for the entire measurements. When classifying into normal/pathological voice classes, the Oral-NNE revealed the CCR of 73.7% and the pair of SP-NNE and SP-shimmer parameters revealed CCR of 79.5%. However, fusion of the results obtained from SP voice recordings and GFI data provided the CCR of 84.60% and RFC revealed the EER of 7.9%, respectively. In conclusion, measurements of acoustic voice parameters using SP microphone were shown to be reliable in clinical settings demonstrating high CCR and low EER when distinguishing normal and pathological voice classes, and validated the suitability of the SP microphone signal for the task of automatic voice analysis and screening. Springer-Verlag Berlin Heidelberg, 2015 Acoustic analysis nationallicence Voice screening nationallicence Smart phone nationallicence Uloza Virgilijus Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut Padervinskis Evaldas Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut Vegiene Aurelija Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut Pribuisiene Ruta Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut Saferis Viktoras Department of Physics, Mathematics and Biophysics, Lithuanian University of Health Sciences, Kaunas, Lithuania aut Vaiciukynas Evaldas Department of Electric Power Systems, Kaunas University of Technology, Kaunas, Lithuania aut Gelzinis Adas Department of Electric Power Systems, Kaunas University of Technology, Kaunas, Lithuania aut Verikas Antanas Department of Electric Power Systems, Kaunas University of Technology, Kaunas, Lithuania aut European Archives of Oto-Rhino-Laryngology Springer Berlin Heidelberg 272/11(2015-11-01), 3391-3399 0937-4477 272:11<3391 2015 272 405 https://doi.org/10.1007/s00405-015-3708-4 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00405-015-3708-4 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Uloza Virgilijus Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Padervinskis Evaldas Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Vegiene Aurelija Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Pribuisiene Ruta Department of Otolaryngology, Lithuanian University of Health Sciences, Eiveniu 2, 50009, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Saferis Viktoras Department of Physics, Mathematics and Biophysics, Lithuanian University of Health Sciences, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Vaiciukynas Evaldas Department of Electric Power Systems, Kaunas University of Technology, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Gelzinis Adas Department of Electric Power Systems, Kaunas University of Technology, Kaunas, Lithuania aut NATIONALLICENCE 700 1- Verikas Antanas Department of Electric Power Systems, Kaunas University of Technology, Kaunas, Lithuania aut NATIONALLICENCE 773 0- European Archives of Oto-Rhino-Laryngology Springer Berlin Heidelberg 272/11(2015-11-01), 3391-3399 0937-4477 272:11<3391 2015 272 405