Coswara — A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis
Neeraj Kumar Sharma, Prashant Krishnan, Rohit Vishal Kumar, Shreyas Ramoji, Srikanth Raj Chetupalli, R. Nirmala, Prasanta Ghosh, Sriram Ganapathy · 2020
The COVID-19 pandemic presents global challenges transcending boundaries of country, race, religion, and economy.The current gold standard method for COVID-19 detection is the reverse transcription polymerase chain reaction (RT-PCR) testing.However, this method is expensive, time-consuming, and violates social distancing.Also, as the pandemic is expected to stay for a while, there is a need for an alternate diagnosis tool which overcomes these limitations, and is deployable at a large scale.The prominent symptoms of COVID-19 include cough and breathing difficulties.We foresee that respiratory sounds, when analyzed using machine learning techniques, can provide useful insights, enabling the design of a diagnostic tool.Towards this, the paper presents an early effort in creating (and analyzing) a database, called Coswara, of respiratory sounds, namely, cough, breath, and voice.The sound samples are collected via worldwide crowdsourcing using a website application.The curated dataset is released as open access.As the pandemic is evolving, the data collection and analysis is a work in progress.We believe that insights from analysis of Coswara can be effective in enabling sound based technology solutions for point-of-care diagnosis of respiratory infection, and in the near future this can help to diagnose COVID-19.