Coswara: A website application enabling COVID-19 screening by analysing respiratory sound samples and health symptoms

Bhattacharya, D and Dutta, D and Sharma, NK and Chetupalli, SR and Mote, P and Ganapathy, S and Chandrakiran, C and Nori, S and Suhail, KK and Gonuguntla, S and Alagesan, M (2022) Coswara: A website application enabling COVID-19 screening by analysing respiratory sound samples and health symptoms. In: 23rd Annual Conference of the International Speech Communication Association, INTERSPEECH 2022, 18 - 22 September 2022, Incheon, pp. 1957-1958.

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Abstract

The COVID-19 pandemic has accelerated research on design of alternative, quick and effective COVID-19 diagnosis approaches. In this paper, we describe the Coswara tool, a website application designed to enable COVID-19 detection by analysing respiratory sound samples and health symptoms. A user using this service can log into a website using any device connected to the internet, provide there current health symptom information and record few sound sampled corresponding to breathing, cough, and speech. Within a minute of analysis of this information on a cloud server the website tool will output a COVID-19 probability score to the user. As the COVID-19 pandemic continues to demand massive and scalable population level testing, we hypothesize that the proposed tool provides a potential solution towards this.

Item Type:	Conference Paper
Publication:	Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH
Publisher:	International Speech Communication Association
Additional Information:	The copyright for this article belongs to International Speech Communication Association.
Keywords:	Screening; Speech communication; Websites, 'current; Breathing; Cloud servers; Cough; Counting; Respiratory sounds; Sound sample; Vowel; WEB application; Web applications, COVID-19
Department/Centre:	Division of Electrical Sciences > Electrical Engineering
Date Deposited:	10 Nov 2022 06:15
Last Modified:	10 Nov 2022 06:15
URI:	https://eprints.iisc.ac.in/id/eprint/77853

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