@article{454947b6831b41459b04320713d14ff4,
title = "A summary of the ComParE COVID-19 challenges",
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{\textquoteright} 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",
author = "Harry Coppock and Alican Akman and Christian Bergler and Maurice Gerczuk and Chlo{\"e} Brown and Jagmohan Chauhan and Andreas Grammenos and Apinan Hasthanasombat and Dimitris Spathis and Tong Xia and Pietro Cicuta and Jing Han and Shahin Amiriparian and Alice Baird and Lukas Stappen and Sandra Ottl and Panagiotis Tzirakis and Anton Batliner and Cecilia Mascolo and Schuller, {Bj{\"o}rn W.}",
note = "Publisher Copyright: 2023 Coppock, Akman, Bergler, Gerczuk, Brown, Chauhan, Grammenos, Hasthanasombat, Spathis, Xia, Cicuta, Han, Amiriparian, Baird, Stappen, Ottl, Tzirakis, Batliner, Mascolo and Schuller.",
year = "2023",
doi = "10.3389/fdgth.2023.1058163",
language = "English",
volume = "5",
journal = "Frontiers in Digital Health",
issn = "2673-253X",
publisher = "Frontiers Media S.A.",
}