Coswara — A Database of Breathing, Cough, and Voice Sounds for COVID-19 Diagnosis

Abstract

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.

Machine and Deep Learning towards COVID-19 Diagnosis and Treatment: Survey, Challenges, and Future Directions

“…The BI-AT-GRU model involves the bidirectional bids and attention of the GRU neural network, and it can differentiate between six forms of clinical respiratory types, such as Eupnea, Tachypnea, Bradypnea, Biots, Cheyne-Stokes, and Central-Apnea. Sharma et al [57] intended to create the laboratory diagnostic techniques of COVID-19 for sputum testing. In roder to test biomarkers in acoustics, the project, called Coswara, used cough, breath, and speech sounds.…”

End-to-end convolutional neural network enables COVID-19 detection from breath and cough audio: a pilot study

“…Throughout the COVID-19 pandemic there have been numerous efforts to compile data sets of breath and cough audio recordings, including ‘Coughvid’, 3 ‘Breathe for Science’ ( https://www.breatheforscience.com ), ‘Coswara’ 4 and ‘CoughAgainstCovid’. 5 With their release, several studies have been published that leverage audio signals alongside machine learning to detect the virus.…”

End-to-End AI-Based Point-of-Care Diagnosis System for Classifying Respiratory Illnesses and Early Detection of COVID-19: A Theoretical Framework

“…They have concluded that it is possible to distinguish COVID-19 cough sounds from healthy cough using a simple binary machine learning classifier. This points to the potential of using cough sounds to diagnose COVID-19 (35)(36)(37). The cough sound can also be used to detect other respiratory illnesses.…”