COVID-19 detection from audio: seven grains of salt
Harry Coppock, Lyn Isobel Jones, Ivan Kiskin, Björn Wolfgang Schuller · The Lancet Digital Health · 2021
Digital mass testing for COVID-19 via a mobile phone application could be made possible through machine learning and its ability to identify patterns in data. COVID-19 appears to confer unique features in the audio produced by infected individuals,1 and machine learning COVID-19 detection from breath, cough, and speech audio recordings has yielded promising results.2–4 In this critique, we present seven major issues with this research and argue that further investigation is needed before conclusions about the detectability of COVID-19 from audio can be made.