Aníbal Ferreira

Abstract
Objectives: To describe the results of the acoustic analysis of a database of 90 voice samples with distinct dysphonia levels, using four different - commercial and open source - software programs. Study design: Exploratory, transversal. Methods: The samples were analyzed by four different types of software programs that perform acoustical evaluation - one open source software (Praat) and three commercial ones (Multi Dimensional Voice Program - MDVP by Kay Elemetrics; VoiceStudio by Seegnal; and Dr. Speech by Tiger Electronics) - for comparison among the most commonly used acoustic measures (frequency, perturbation and noise measures). Results: There is a moderate to strong,correlation, positive and statistically significant among the software programs. The mean FO is not statistically different among the used applications. The other acoustic measures revealed statistically significant differences. Conclusion: Even though it is easier to access software programs and there are numerous proposals for acoustic measures, not all of them are statistically representative nor have numeric semblance among the different applications.

Abstract
The incidence of chronic diseases is increasing and monitoring patients in a home environment is recommended. Noncompliance with prescribed medication regimens is a concern, especially among older people. Heart failure is a chronic disease that requires patients to follow strict medication plans permanently. With the objective of helping these patients managing information about their medicines and increasing adherence, the personal medication advisor CARMIE was developed as a conversational agent capable of interacting, in Portuguese, with users through spoken natural language. The system architecture is based on a language parser, a dialog manager, and a language generator, integrated with already existing tools for speech recognition and synthesis. All modules work together and interact with the user through an Android application, supporting users to manage information about their prescribed medicines. The authors also present a preliminary usability study and further considerations on CARMIE. Copyright © 2017, IGI Global.

Abstract
The incidence of chronic diseases is increasing and monitoring patients in a home environment is recommended. Noncompliance with prescribed medication regimens is a concern, especially among older people. Heart failure is a chronic disease that requires patients to follow strict medication plans permanently. With the objective of helping these patients managing information about their medicines and increasing adherence, the personal medication advisor CARMIE was developed as a conversational agent capable of interacting, in Portuguese, with users through spoken natural language. The system architecture is based on a language parser, a dialog manager, and a language generator, integrated with already existing tools for speech recognition and synthesis. All modules work together and interact with the user through an Android application, supporting users to manage information about their prescribed medicines. The authors also present a preliminary usability study and further considerations on CARMIE. © 2018, IGI Global.

Abstract
The goal of this study was to analyse perceptually and acoustically the voices of patients with Unilateral Vocal Fold Paralysis (UVFP) and compare them to the voices of normal subjects. These voices were analysed perceptually with the GRBAS scale and acoustically using the following parameters: mean fundamental frequency (F0), standard-deviation of F0, jitter (ppq5), shimmer (apq11), mean harmonics-to-noise ratio (HNR), mean first (F1) and second (F2) formants frequency, and standard-deviation of F1 and F2 frequencies. Statistically significant differences were found in all of the perceptual parameters. Also the jitter, shimmer, HNR, standard-deviation of F0, and standard-deviation of the frequency of F2 were statistically different between groups, for both genders. In the male data differences were also found in F1 and F2 frequencies values and in the standard-deviation of the frequency of F1. This study allowed the documentation of the alterations resulting from UVFP and addressed the exploration of parameters with limited information for this pathology.

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-a(2) = 0.17) to moderate (R-a(2) = 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.