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 d...

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Autores principales: 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.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Frontiers Media S.A. 2023
Materias:
Digital Health
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031089/
https://www.ncbi.nlm.nih.gov/pubmed/36969956
http://dx.doi.org/10.3389/fdgth.2023.1058163
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author 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.
author_facet 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.
author_sort Coppock, Harry
collection PubMed
description 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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spelling pubmed-100310892023-03-23 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. Front Digit Health Digital Health 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). Frontiers Media S.A. 2023-03-08 /pmc/articles/PMC10031089/ /pubmed/36969956 http://dx.doi.org/10.3389/fdgth.2023.1058163 Text en © 2023 Coppock, Akman, Bergler, Gerczuk, Brown, Chauhan, Grammenos, Hasthanasombat, Spathis, Xia, Cicuta, Han, Amiriparian, Baird, Stappen, Ottl, Tzirakis, Batliner, Mascolo and Schuller. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY) (https://creativecommons.org/licenses/by/4.0/) . The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
spellingShingle Digital Health
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.
A summary of the ComParE COVID-19 challenges
title A summary of the ComParE COVID-19 challenges
title_full A summary of the ComParE COVID-19 challenges
title_fullStr A summary of the ComParE COVID-19 challenges
title_full_unstemmed A summary of the ComParE COVID-19 challenges
title_short A summary of the ComParE COVID-19 challenges
title_sort summary of the compare covid-19 challenges
topic Digital Health
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10031089/
https://www.ncbi.nlm.nih.gov/pubmed/36969956
http://dx.doi.org/10.3389/fdgth.2023.1058163
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