The Second Dicova Challenge: Dataset and Performance Analysis for Diagnosis of Covid-19 Using Acoustics

Author:

Sharma Neeraj Kumar1,Chetupalli Srikanth Raj1,Bhattacharya Debarpan1,Dutta Debottam1,Mote Pravin1,Ganapathy Sriram1

Affiliation:

1. Indian Institute of Science,LEAP Lab,Bangalore,India,560012

Publisher

IEEE

Reference22 articles.

1. COVID-19 Artificial Intelligence Diagnosis Using Only Cough Recordings

2. Coswara – a database of breathing, cough, and voice sounds for COVID-19 diagnosis;sharma;Proc INTERSPEECH,2020

3. DiCOVA Challenge: Dataset, Task, and Baseline System for COVID-19 Diagnosis Using Acoustics

4. Towards sound based testing of covid-19–summary of the first diagnostics of covid-19 using acoustics (dicova) challenge;sharma,2021

5. Cambridge University, UK - COVID-19 Sounds App,2020

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1. Spectral–temporal saliency masks and modulation tensorgrams for generalizable COVID-19 detection;Computer Speech & Language;2024-06

2. On the Impact of Voice Anonymization on Speech Diagnostic Applications: A Case Study on COVID-19 Detection;IEEE Transactions on Information Forensics and Security;2024

3. C3-PO: A Convolutional Neural Network for COVID Onset Prediction from Cough Sounds;Lecture Notes in Computer Science;2024

4. Coswara: A respiratory sounds and symptoms dataset for remote screening of SARS-CoV-2 infection;Scientific Data;2023-06-22

5. COVID-19 Detection from Speech in Noisy Conditions;ICASSP 2023 - 2023 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP);2023-06-04

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