Susana Vaz Freitas1, Pedro Melo Pestana2, Vítor Almeida3, Aníbal Ferreira3. 1. Serviço de Otorrinolaringologia, Centro Hospitalar do Porto, Largo Prof. Abel Salazar, Porto, Portugal; Speech Therapy Department-Faculty of Health Sciences, Universidade Fernando Pessoa, Porto, Portugal; Biomedical Engineering Department-Faculty of Engineering, Universidade do Porto, Porto, Portugal. Electronic address: svazfreitas@gmail.com. 2. Unidade de Cuidados Continuados de Longa Duração e Manutenção da Gelfa, Vila Praia de Âncora, Portugal. 3. Electric and Computer Engineering Department-Faculty of Engineering, Universidade do Porto, Rua Doutor Roberto Frias, Porto, Portugal.
Abstract
OBJECTIVES/HYPOTHESIS: This article aims to establish correlations between acoustic and audio-perceptual measures using the GRBAS scale with respect to four different voice analysis software programs. STUDY DESIGN: Exploratory, transversal. METHODS: A total of 90 voice records were collected and analyzed with the Dr. Speech (Tiger Electronics, Seattle, WA), Multidimensional Voice Program (Kay Elemetrics, NJ, USA), PRAAT (University of Amsterdam, The Netherlands), and Voice Studio (Seegnal, Oporto, Portugal) software programs. The acoustic measures were correlated to the audio-perceptual parameters of the GRBAS and rated by 10 experts. RESULTS: The predictive value of the acoustic measurements related to the audio-perceptual parameters exhibited magnitudes ranging from weak (R(2)a=0.17) to moderate (R(2)a=0.71). The parameter exhibiting the highest correlation magnitude is B (Breathiness), whereas the weaker correlation magnitudes were found to be for A (Asthenia) and S (Strain). The acoustic measures with stronger predictive values were local Shimmer, harmonics-to-noise ratio, APQ5 shimmer, and PPQ5 jitter, with different magnitudes for each one of the studied software programs. CONCLUSIONS: Some acoustic measures are pointed as significant predictors of GRBAS parameters, but they differ among software programs. B (Breathiness) was the parameter exhibiting the highest correlation magnitude.
OBJECTIVES/HYPOTHESIS: This article aims to establish correlations between acoustic and audio-perceptual measures using the GRBAS scale with respect to four different voice analysis software programs. STUDY DESIGN: Exploratory, transversal. METHODS: A total of 90 voice records were collected and analyzed with the Dr. Speech (Tiger Electronics, Seattle, WA), Multidimensional Voice Program (Kay Elemetrics, NJ, USA), PRAAT (University of Amsterdam, The Netherlands), and Voice Studio (Seegnal, Oporto, Portugal) software programs. The acoustic measures were correlated to the audio-perceptual parameters of the GRBAS and rated by 10 experts. RESULTS: The predictive value of the acoustic measurements related to the audio-perceptual parameters exhibited magnitudes ranging from weak (R(2)a=0.17) to moderate (R(2)a=0.71). The parameter exhibiting the highest correlation magnitude is B (Breathiness), whereas the weaker correlation magnitudes were found to be for A (Asthenia) and S (Strain). The acoustic measures with stronger predictive values were local Shimmer, harmonics-to-noise ratio, APQ5 shimmer, and PPQ5 jitter, with different magnitudes for each one of the studied software programs. CONCLUSIONS: Some acoustic measures are pointed as significant predictors of GRBAS parameters, but they differ among software programs. B (Breathiness) was the parameter exhibiting the highest correlation magnitude.