This work is licensed under a Creative Commons Attribution 4.0 International (CC BY 4.0) License.
UPDATE: The current full version of Coswara data is now published with open access in Nature Scientific Data, 2023. read
Project Coswara by Indian Institute of Science (IISc) Bangalore is an attempt to build a diagnostic tool for COVID-19 detection using the audio recordings such as breathing, cough and speech sounds of an individual. Currently, the project is in the data collection stage through crowdsourcing. To contribute your audio samples, please go to Project Coswara(https://coswara.iisc.ac.in/). The exercise takes 5-7 minutes.
What am I looking at? This github repository contains the raw audio data collected through https://coswara.iisc.ac.in/ . Every participant contributes nine sound samples. You can read the paper: Coswara - A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis to know more about the dataset. Note that the dataset size has increased since this paper came out. We also maintain a (less frequently updated) blog here.
What is the structure of the repository?
Each folder contains metadata and audio recordings corresponding to contributors. The folder is compressed. To download and extract the data, you can run the script extract_data.py
What are the different sound samples? Sound samples collected include breathing sounds (fast and slow), cough sounds (deep and shallow), phonation of sustained vowels (/a/ as in made, /i/,/o/), and counting numbers at slow and fast pace. Metadata information collected includes the participant's age, gender, location (country, state/ province), current health status (healthy/ exposed/ positive/recovered) and the presence of comorbidities (pre-existing medical conditions).
Can I see the metadata before downloading whole repository?
Yes. The file combined_data.csv
contains a summary of metadata. The file csv_labels_legend.json
contains information about the columns present in combined_data.csv
.
Is there any audio quality check?
Yes. The audio files are manually listened and labeled as one of the three categories: 2(excellent), 1(good), 0(bad). The labels are present in the annotations
folder.
How to cite this dataset in your work? Great to know you found it useful. You can cite the paper: Coswara - A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis (https://arxiv.org/abs/2005.10548)
Is there any web application for COVID-19 screening based on respiratory acoustics? Yes! One can record his/her respiratory sounds at Coswara web application and obtain a COVID-19 probability score in few seconds. Demo: here, paper: here
What is the count of participants in each folder?
Each folder also has a CSV file which contains metadata of each sample (that is, participant).
Can I know the individuals maintaining this project? Yes, we are a team of Professors, PostDocs, Engineers, and Research Scholars affiliated with the Indian Institute of Science, Bangalore (India). Sriram Ganapathy, Assistant Professor, Dept. Electrical Engineering, IISc is the Principal Investigator of this project.
Current Members: Debarpan Bhattacharya, Neeraj Kumar Sharma, Prasanta Kumar Ghosh, Srikanth Raj Chetupalli, Sriram Ganapathy
Past Members: Anand Mohan, Ananya Muguli, Debottam Dutta, Prashant Krishnan, Pravin Mote, Rohit Kumar, Shreyas Ramoji
(arranged in alphabetical order)