A summary of the ComParE COVID-19 challenges

Harry Coppock; Alican Akman; Christian Bergler; Maurice Gerczuk; Chloë Brown; Jagmohan Chauhan; Andreas Grammenos; Apinan Hasthanasombat; Dimitris Spathis; Tong Xia; Pietro Cicuta; Jing Han; Shahin Amiriparian; Alice Baird; Lukas Stappen; Sandra Ottl; Panagiotis Tzirakis; Anton Batliner; Cecilia Mascolo; Björn W. Schuller

doi:10.3389/fdgth.2023.1058163

A summary of the ComParE COVID-19 challenges

Harry Coppock, Alican Akman, Christian Bergler, Maurice Gerczuk, Chloë Brown, Jagmohan Chauhan, Andreas Grammenos, Apinan Hasthanasombat, Dimitris Spathis, Tong Xia, Pietro Cicuta, Jing Han, Shahin Amiriparian, Alice Baird, Lukas Stappen, Sandra Ottl, Panagiotis Tzirakis, Anton Batliner, Cecilia Mascolo, Björn W. Schuller

Research output: Contribution to journal › Article › peer-review

2 Scopus citations

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).

Original language	English
Article number	1058163
Journal	Frontiers in Digital Health
Volume	5
DOIs	https://doi.org/10.3389/fdgth.2023.1058163
State	Published - 2023
Externally published	Yes

Keywords

COVID-19
Digital Health
computer audition
deep learning
machine learning

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10.3389/fdgth.2023.1058163

Cite this

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, B. W. (2023). A summary of the ComParE COVID-19 challenges. Frontiers in Digital Health, 5, Article 1058163. https://doi.org/10.3389/fdgth.2023.1058163

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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.",

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doi = "10.3389/fdgth.2023.1058163",

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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, 'A summary of the ComParE COVID-19 challenges', Frontiers in Digital Health, vol. 5, 1058163. https://doi.org/10.3389/fdgth.2023.1058163

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T1 - A summary of the ComParE COVID-19 challenges

AU - Coppock, Harry

AU - Akman, Alican

AU - Bergler, Christian

AU - Gerczuk, Maurice

AU - Brown, Chloë

AU - Chauhan, Jagmohan

AU - Grammenos, Andreas

AU - Hasthanasombat, Apinan

AU - Spathis, Dimitris

AU - Xia, Tong

AU - Cicuta, Pietro

AU - Han, Jing

AU - Amiriparian, Shahin

AU - Baird, Alice

AU - Stappen, Lukas

AU - Ottl, Sandra

AU - Tzirakis, Panagiotis

AU - Batliner, Anton

AU - Mascolo, Cecilia

AU - Schuller, Björn W.

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PY - 2023

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AB - 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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KW - machine learning

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JO - Frontiers in Digital Health

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ER -

A summary of the ComParE COVID-19 challenges

Abstract

Keywords

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