Since the outbreak of COVID-19, many efforts have been made to utilize the respiratory
sounds and coughs collected by smartphones for training Machine Learning models to …

Objective To investigate the association of voice analysis with severe acute respiratory
syndrome coronavirus 2 (SARS-CoV-2) infection. Patients and Methods A vocal biomarker …

COVID-19 heavily affects breathing and voice and causes symptoms that make patients'
voices distinctive, creating recognizable audio signatures. Initial studies have already …

Automated voice-based detection of severe acute respiratory syndrome coronavirus 2
(SARS-CoV-2) could facilitate the screening for COVID19. A dataset of cellular phone …

Abstract The UK COVID-19 Vocal Audio Dataset is designed for the training and evaluation
of machine learning models that classify SARS-CoV-2 infection status or associated …

Purpose The ongoing literature suggests that COVID-19 may have a potential impact on
voice characteristics during the infection period. In the current study, we explored how the …

This study aimed to develop an artificial intelligence (AI)-based tool for screening COVID-19
patients based on the acoustic parameters of their voices. Twenty-five acoustic parameters …

Background Vocal biomarker–based machine learning approaches have shown promising
results in the detection of various health conditions, including respiratory diseases, such as …

Healthcare sensors represent a valid and non-invasive instrument to capture and analyse
physiological data. Several vital signals, such as voice signals, can be acquired anytime and …

Audio classification using breath and cough samples has recently emerged as a low-cost,
non-invasive, and accessible COVID-19 screening method. However, a comprehensive …