“…Acoustic phonation studies provide relevant speaker information that can be used to detect diseases such as Alzheimer's dementia, Parkinson's, and amyotrophic lateral sclerosis, among others, based on the biomechanical uniqueness of each individual. Such uniqueness is evident in the EWA-DB dataset, which focuses on Slovak speakers with Alzheimer's and Parkinson's diseases (Rusko et al, 2023), and a dataset that focuses on Spanish native speakers with Parkinson's disease (Orozco-Arroyave et al, 2014), as well as recent acoustic studies on Alzheimer's (Cai et al, 2023;Zolnoori et al, 2023) and Parkinson's (Warule et al, 2023) diseases. In the 2021 study by Lee (2021), two types of neural network models were developed for dysphonia detection: a Feedforward Neural Network (FNN) and a Convolutional Neural Network (CNN).…”