The COVID-19 pandemic has resulted in more than 200 million infections, and more than 4 million casualties. Although the case-to--fatality ratio (CFR) is less than 1/5th of that in the influenza pandemic in 1928, in the current age of science and technology, these figures are worrying. The pathogenesis of COVID-19 is increasingly suggesting impairments in the respiratory system. In this light, it is natural to ask - Can sound samples serve as acoustic biomarkers of COVID-19? If yes, an acoustics based COVID-19 diagnosis can provide a fast, contactless and inexpensive testing scheme, with potential to supplement the existing molecular testing methods, such as RT-PCR and RAT. The DiCOVA Challenge Series is an exploration of ideas to find answers to this question.
Considering the immediate societal relevance of a technology driven point-of-care-test (POCT) for COVID-19, the DiCOVA Challenge has three aims. Release a curated dataset of sound samples (breathing, cough, and speech) drawn from individuals with and without COVID-19 during the time of recording. Invite researchers from around the globe to search for acoustic biomarkers in this dataset. Evaluate the findings of each group using a blind test set, and present a competitive leaderboard with global participation.

Building on the overwhelming response to the first DiCOVA Challenge, we are excited to launch this Second DiCOVA Challenge with the following updates. Larger dataset: Over the past few months we have created an audio dataset with an improved ratio of COVID-19-to-non-COVID subjects. Multi-modality: In addition to the cough sound samples used in the first DiCOVA challenge, recent research indicates the COVID-19 acoustic signature can be also extracted from breathing and speech sound samples. The second DiCOVA challenge will feature three sound categories (cough, speech and breathing) and four tracks (three individual categories and one fusion). A leaderboard will be set to track the performance as done in the previous challenge. Enhanced Pre-training: Several open source and publicly available cough datasets have been published recently. The challenge participants will be encouraged to use these datasets to pre-train their models for improved performance. We are hopeful, this will open up new horizons for focussed and timely effort from researchers on a topic at the interface of acoustics, signal processing, and healthcare.
We look forward to your participation!

  • [05-Oct-21] Challenge Closed. The final Leaderboard is available at: Click here.
  • [05-Oct-21] Challenge Baseline Paper is available at: Click here.
  • [08-Sep-21] Challenge Leaderboard is live now! Click here.
  • [07-Sep-21] Evaluation dataset has been sent to all registered participants.
  • [26-Aug-21] Development dataset, and baseline system software has been sent to all registered participants.
  • [16-Aug-21] Click here to download the flyer.

Prior to this challenge, the first DiCOVA Challenge was launched on Feb 04, 2021. It focussed on COVID-19 detection using only cough sounds. The challenge received an enthusiatic response from the research community across industry and acadmia. The challenge closed on Mar 23, 2021. A summary of results is provided here and here.

Timeline (Tentative) [23:59hrs AOE]

Registrations Open :
12th Aug 2021
Registrations Close:
25th Aug 2021 10th Sep 2021
Data Release (Dev):
16th Aug 2021 18th Aug 2021
Baseline System Release:
23rd Aug 2021
Evaluation data and Leaderboard active:
30th Aug 2021 7th Sep 2021
Final evaluation Closes:
24th Sep 2021 1st Oct 2021
System Report submission:
2nd Oct 2021
ICASSP Paper Submission Closes:
1st Oct 2021 6th Oct 2021 (follow updates at: click here)


The challenge features four tracks. The first three tracks focus on single sound categories, and the fourth track is a fusion track. The task is to design a binary classifier for COVID-19 detection.

Breathing Sound Samples
Cough Sound Samples
Speech Sound Samples
Fusion. Here participants can use any combination of above sound categories.

Click to know more

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  • b. You will be provided with a train/val audio dataset, train/val lists, and a baseline system to facilitate design of your own classifier models.
  • c. Subsequently, a blind test set will be provided for model evaluation. You will submit your model performance scores on the blind set and the validation lists to a leaderboard interface (setup in Codalab) featuring performance of other teams on the same dataset.
  • d. The performance metric for evaluation will be based on using the area under the receiver opertaing characteristic curve (AUC) and the specificity at 80% sensitivity.
  • e. All participants will be required to submit a system description report (2-4 pages) to the organizers.
  • f. You are free to use any other dataset but excluding the Project Coswara dataset) for data augmentation.

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Thank you for your interest! Below are the two quick steps involved in registering your participation and get started in the challenge.
One representative of the participating team fills the form at: click here
Subsequently, fill the Terms and Conditions and e-mail it to us at dicova.challenge@gmail.com
After a quick verification of the submitted details, we will confirm your registration within 24 hrs. That's it!


Sriram Ganapathy
Assistant Professor, Indian Institute of Science, Bangalore, India
Prasanta Kumar Ghosh
Assistant Professor, Indian Institute of Science, Bangalore, India
Neeraj Kumar Sharma
CV Raman Postdoctoral Researcher, Indian Institute of Science, Bangalore, India
Srikanth Raj Chetupalli
Postdoctoral Researcher, Indian Institute of Science, Bangalore, India
Debarpan Bhattacharya
MTech Scholar, Indian Institute of Science, Bangalore, India
Debottam Dutta
Research Associate, Indian Institute of Science, Bangalore, India
Pravin Mote
Senior Research Fellow, Indian Institute of Science, Bangalore, India

Frequently Asked Questions

Q. Which programming languages can I use?

A. You are free to use any programming language you like. For system evaluation we will require you to submit the output decisions as a CSV/TXT file.
Q. How do I get the DiCOVA audio dataset?

A. It is simple - by registering for the challenge. Please see the registration section in this webpage (above).
Q. Can I re-distribute the data?

A. Yes but only after obtaining consent of the organizers.
Q. Can I obtain/use the DiCOVA audio data without participating in the challenge?

A. No. We might re-consider this answer after the end of the challenge. Please contact us then.

Contact Us

You have more questions? Feel free to contact us at: x@y.com where x is dicova.challenge and y is gmail.