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• W4323567384 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)." @default.
• W4323567384 created "2023-03-09" @default.
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• W4323567384 date "2023-03-08" @default.
• W4323567384 modified "2023-10-11" @default.
• W4323567384 title "A summary of the ComParE COVID-19 challenges" @default.
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• W4323567384 doi "https://doi.org/10.3389/fdgth.2023.1058163" @default.
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• W4323567384 hasPublicationYear "2023" @default.
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