The coronavirus disease 2019 (COVID 19!) pandemic, which is the hottest topic in the last 1.5 years, deeply affects people's lives all over the world. Early diagnosis, taking into account the symptoms, is crucial to surviving this devastating catastrophe. Thanks to this early diagnosis, the rapid spread of the virus can be slowed or even stopped. Although effective vaccines against the virus were put forward while writing this article, it is not overlooked that the virus mutates rapidly in various variants. The most common symptoms of COVID-19 include fatigue, fever, dry cough. The Reverse Transcription Polymer Chain Reaction (RT-PCR) test used for coronavirus diagnosis is costly, time-consuming, and also not easily accessible. In this sense, COVID-19 early diagnosis studies are pushed researchers in different directions. One of these aspects is the signal processing of the cough sound. It has been the focus of many scientific studies that the cough sound has a great role in the diagnosis of respiratory diseases. In order to overcome the COVID-19 crisis, signal processing and artificial intelligence-based studies have started to become widespread. In this study, a short dive was made into the data sets of studies based on COVID-19 cough sounds based on the cough symptom. The main purpose of the research is to bring together studies based on cough sounds for the early diagnosis of COVID-19 and to present a detailed comparison study in the use of feature extraction and classification algorithms, which are a step in the field of signal processing. © 2021 IEEE.
A Brief Dive into COVID-19 Cough Sound Data sets