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A summary of the ComParE COVID-19 challenges.
Coppock, Harry; Akman, Alican; Bergler, Christian; Gerczuk, Maurice; Brown, Chloë; Chauhan, Jagmohan; Grammenos, Andreas; Hasthanasombat, Apinan; Spathis, Dimitris; Xia, Tong; Cicuta, Pietro; Han, Jing; Amiriparian, Shahin; Baird, Alice; Stappen, Lukas; Ottl, Sandra; Tzirakis, Panagiotis; Batliner, Anton; Mascolo, Cecilia; Schuller, Björn W.
  • Coppock H; Department of Computing, Imperial College London, London, United Kingdom.
  • Akman A; Department of Computing, Imperial College London, London, United Kingdom.
  • Bergler C; Department of Computing, FAU Erlangen-Nürnberg, Erlangen-Nürnberg, Germany.
  • Gerczuk M; Institute of Computer Science, Universität Augsburg, Augsburg, Germany.
  • Brown C; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Chauhan J; Department of Computing, University of Southampton, Southampton, United Kingdom.
  • Grammenos A; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Hasthanasombat A; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Spathis D; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Xia T; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Cicuta P; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Han J; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Amiriparian S; Institute of Computer Science, Universität Augsburg, Augsburg, Germany.
  • Baird A; Institute of Computer Science, Universität Augsburg, Augsburg, Germany.
  • Stappen L; Institute of Computer Science, Universität Augsburg, Augsburg, Germany.
  • Ottl S; Institute of Computer Science, Universität Augsburg, Augsburg, Germany.
  • Tzirakis P; Department of Computing, Imperial College London, London, United Kingdom.
  • Batliner A; Institute of Computer Science, Universität Augsburg, Augsburg, Germany.
  • Mascolo C; Department of Computer Science and Technology, University of Cambridge, Cambridge, United Kingdom.
  • Schuller BW; Department of Computing, Imperial College London, London, United Kingdom.
Front Digit Health ; 5: 1058163, 2023.
Article in English | MEDLINE | ID: covidwho-2255581
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).
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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Front Digit Health Year: 2023 Document Type: Article Affiliation country: Fdgth.2023.1058163

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Full text: Available Collection: International databases Database: MEDLINE Language: English Journal: Front Digit Health Year: 2023 Document Type: Article Affiliation country: Fdgth.2023.1058163