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Communication Dans Un Congrès Année : 2021

Cough sound recognition for COVID-19 risk detection

Marine Diniz
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Vincent Zalc
Dan Istrate

Résumé

The COVID-19 outbreak prompts the need for new ways to detect and prevent epidemics. Since cough is one of the COVID-19 symptoms, our work proposes a sound recognition system based on our previous works which are able to detect different type of cough through a continuously home sound analysis. It is a part of EpiSemioWatch AMI COVID UTC funded project which aims to develop a detection system of epidemic risk in retirement home using sound and movement sensors. This paper presents the sound part of the global system and more explicitly the differentiation of cough from other environmental sound. The proposed system detects automatically the sound activity through a wavelet based system, realize an acoustic segmentation speech/sound and classify the cough sounds. A first evaluation of the system in our lab is presented.
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Dates et versions

hal-03501195 , version 1 (23-12-2021)

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Citer

Marine Diniz, Vincent Zalc, Dan Istrate. Cough sound recognition for COVID-19 risk detection. JETSAN 2021 - Colloque en Télésanté et dispositifs biomédicaux - 8ème édition, Université Toulouse III - Paul Sabatier [UPS], May 2021, Toulouse, Blagnac, France. ⟨10.34746/v7mv-4x55⟩. ⟨hal-03501195⟩
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