A summary of the ComParE COVID-19 challenges
A summary of the ComParE COVID-19 challenges
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).
computer audition, COVID-19, deep learning, Digital Health, machine learning
Coppock, Harry
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Akman, Alican
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Bergler, Christian
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Gerczuk, Maurice
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Brown, Chloë
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Chauhan, Jagmohan
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Grammenos, Andreas
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Hasthanasombat, Apinan
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Spathis, Dimitris
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Xia, Tong
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Cicuta, Pietro
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Han, Jing
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Amiriparian, Shahin
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Baird, Alice
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Stappen, Lukas
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Ottl, Sandra
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Tzirakis, Panagiotis
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Batliner, Anton
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Mascolo, Cecilia
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Schuller, Björn W.
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8 March 2023
Coppock, Harry
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Akman, Alican
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Bergler, Christian
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Gerczuk, Maurice
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Brown, Chloë
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Chauhan, Jagmohan
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Grammenos, Andreas
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Hasthanasombat, Apinan
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Spathis, Dimitris
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Xia, Tong
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Cicuta, Pietro
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Han, Jing
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Amiriparian, Shahin
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Baird, Alice
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Stappen, Lukas
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Ottl, Sandra
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Tzirakis, Panagiotis
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Batliner, Anton
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Mascolo, Cecilia
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Schuller, Björn W.
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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 and Schuller, Björn W.
(2023)
A summary of the ComParE COVID-19 challenges.
Frontiers in Digital Health, 5, [1058163].
(doi:10.3389/fdgth.2023.1058163).
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).
Text
fdgth-05-1058163
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More information
Accepted/In Press date: 9 January 2023
Published date: 8 March 2023
Keywords:
computer audition, COVID-19, deep learning, Digital Health, machine learning
Identifiers
Local EPrints ID: 491126
URI: http://eprints.soton.ac.uk/id/eprint/491126
PURE UUID: 5447748b-f0d3-4b8c-adc8-ca18fe404d9b
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Date deposited: 13 Jun 2024 16:36
Last modified: 13 Jun 2024 16:37
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Contributors
Author:
Harry Coppock
Author:
Alican Akman
Author:
Christian Bergler
Author:
Maurice Gerczuk
Author:
Chloë Brown
Author:
Jagmohan Chauhan
Author:
Andreas Grammenos
Author:
Apinan Hasthanasombat
Author:
Dimitris Spathis
Author:
Tong Xia
Author:
Pietro Cicuta
Author:
Jing Han
Author:
Shahin Amiriparian
Author:
Alice Baird
Author:
Lukas Stappen
Author:
Sandra Ottl
Author:
Panagiotis Tzirakis
Author:
Anton Batliner
Author:
Cecilia Mascolo
Author:
Björn W. Schuller
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