A summary of the ComParE COVID-19 challenges

Coppock H, Akman A, Bergler C, Gerczuk M, Brown C, Chauhan J, Grammenos A, Hasthanasombat A, Spathis D, Xia T, Cicuta P, Han J, Amiriparian S, Baird A, Stappen L, Ottl S, Tzirakis P, Batliner A, Mascolo C, Schuller BW (2023)

Publication Type: Journal article

Publication year: 2023


Book Volume: 5

Article Number: 1058163

DOI: 10.3389/fdgth.2023.1058163


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).

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Coppock, H., Akman, A., Bergler, C., Gerczuk, M., Brown, C., Chauhan, J.,... Schuller, B.W. (2023). A summary of the ComParE COVID-19 challenges. Frontiers in Digital Health, 5. https://doi.org/10.3389/fdgth.2023.1058163


Coppock, Harry, et al. "A summary of the ComParE COVID-19 challenges." Frontiers in Digital Health 5 (2023).

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