A summary of the ComParE COVID-19 challenges

Front Digit Health. 2023 Mar 8:5:1058163. doi: 10.3389/fdgth.2023.1058163. eCollection 2023.

Abstract

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).

Keywords: COVID-19; Digital Health; computer audition; deep learning; machine learning.

Grants and funding

We acknowledge funding from the DFG’s Reinhart Koselleck project No. 442218748 (AUDI0NOMOUS) and the ERC project No. 833296 (EAR).