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A large-scale and PCR-referenced vocal audio dataset for COVID-19

Authors :
Budd, Jobie
Baker, Kieran
Karoune, Emma
Coppock, Harry
Patel, Selina
Cañadas, Ana Tendero
Titcomb, Alexander
Payne, Richard
Hurley, David
Egglestone, Sabrina
Butler, Lorraine
Mellor, Jonathon
Nicholson, George
Kiskin, Ivan
Koutra, Vasiliki
Jersakova, Radka
McKendry, Rachel A.
Diggle, Peter
Richardson, Sylvia
Schuller, Björn W.
Gilmour, Steven
Pigoli, Davide
Roberts, Stephen
Packham, Josef
Thornley, Tracey
Holmes, Chris
Publication Year :
2022

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 respiratory symptoms using vocal audio. The UK Health Security Agency recruited voluntary participants through the national Test and Trace programme and the REACT-1 survey in England from March 2021 to March 2022, during dominant transmission of the Alpha and Delta SARS-CoV-2 variants and some Omicron variant sublineages. Audio recordings of volitional coughs, exhalations, and speech were collected in the 'Speak up to help beat coronavirus' digital survey alongside demographic, self-reported symptom and respiratory condition data, and linked to SARS-CoV-2 test results. The UK COVID-19 Vocal Audio Dataset represents the largest collection of SARS-CoV-2 PCR-referenced audio recordings to date. PCR results were linked to 70,794 of 72,999 participants and 24,155 of 25,776 positive cases. Respiratory symptoms were reported by 45.62% of participants. This dataset has additional potential uses for bioacoustics research, with 11.30% participants reporting asthma, and 27.20% with linked influenza PCR test results.<br />Comment: 39 pages, 4 figures

Details

Database :
arXiv
Publication Type :
Report
Accession number :
edsarx.2212.07738
Document Type :
Working Paper