A literature review on COVID-19 disease diagnosis from respiratory sound data

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