A Summary of the ComParE COVID-19 Challenges
This work addresses the need for accessible COVID-19 detection methods, but it is incremental as it summarizes existing challenge results rather than introducing new methods.
The paper summarizes results from the INTERSPEECH 2021 Computational Paralinguistics Challenges, which tackled the problem of detecting COVID-19 from respiratory sounds like cough and speech, aiming to develop digital mass tests to combat the pandemic.
The COVID-19 pandemic has caused massive humanitarian and economic damage. Teams of scientists from a broad range of disciplines have searched for methods to help governments and communities combat the disease. One avenue from the machine learning field which has been explored is the prospect of a digital mass test which can detect COVID-19 from infected individuals' respiratory sounds. We present a summary of the results from the INTERSPEECH 2021 Computational Paralinguistics Challenges: COVID-19 Cough, (CCS) and COVID-19 Speech, (CSS).