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THE SECOND DICOVA CHALLENGE: DATASET AND PERFORMANCE ANALYSIS FOR DIAGNOSIS OF COVID-19 USING ACOUSTICS

Sharma, NK and Chetupalli, SR and Bhattacharya, D and Dutta, D and Mote, P and Ganapathy, S (2022) THE SECOND DICOVA CHALLENGE: DATASET AND PERFORMANCE ANALYSIS FOR DIAGNOSIS OF COVID-19 USING ACOUSTICS. In: 47th IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2022, 23 - 27 May 2022, Virtual, Online at Singapore, pp. 556-560.

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Official URL: https://doi.org/10.1109/ICASSP43922.2022.9747188

Abstract

The Second Diagnosis of COVID-19 using Acoustics (DiCOVA) Challenge aimed at accelerating the research in acoustics based detection of COVID-19, a topic at the intersection of acoustics, signal processing, machine learning, and healthcare. This paper presents the details of the challenge, which was an open call for researchers to analyze a dataset of audio recordings consisting of breathing, cough and speech signals. This data was collected from individuals with and without COVID-19 infection, and the task in the challenge was a two-class classification. The development set audio recordings were collected from 965 (172 COVID-19 positive) individuals, while the evaluation set contained data from 471 individuals (71 COVID-19 positive). The challenge featured four tracks, one associated with each sound category of cough, speech and breathing, and a fourth fusion track. A baseline system was also released to benchmark the participants. In this paper, we present an overview of the challenge, the rationale for the data collection and the baseline system. Further, a performance analysis for the systems submitted by the 21 participating teams in the leaderboard is also presented. © 2022 IEEE

Item Type: Conference Paper
Publication: ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publisher: Institute of Electrical and Electronics Engineers Inc.
Additional Information: The copyright for this article belongs to the Institute of Electrical and Electronics Engineers Inc.
Department/Centre: Division of Electrical Sciences > Electrical Engineering
Date Deposited: 21 Jun 2022 10:29
Last Modified: 21 Jun 2022 10:29
URI: https://eprints.iisc.ac.in/id/eprint/73937

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