  The World Health Organization (WHO) has announced a COVID-19 was a global
pandemic in March 2020. It was initially started in china in the year 2019
December and affected an expanding number of nations in various countries in
the last few months. In this particular situation, many techniques, methods,
and AI-based classification algorithms are put in the spotlight in reacting to
fight against it and reduce the rate of such a global health crisis. COVID-19's
main signs are heavy temperature, different cough, cold, breathing shortness,
and a combination of loss of sense of smell and chest tightness. The digital
world is growing day by day, in this context digital stethoscope can read all
of these symptoms and diagnose respiratory disease. In this study, we majorly
focus on literature reviews of how SARS-CoV-2 is spreading and in-depth
analysis of the diagnosis of COVID-19 disease from human respiratory sounds
like cough, voice, and breath by analyzing the respiratory sound parameters. We
hope this review will provide an initiative for the clinical scientists and
researcher's community to initiate open access, scalable, and accessible work
in the collective battle against COVID-19.
