I. Introduction
The COVID-19 pandemic has presented unprecedented challenges to global healthcare systems, demanding innovative approaches for efficient and accurate detection of the virus. With the advancements in technology and the increasing availability of large-scale data, machine learning techniques have emerged as a promising tool in the fight against COVID-19. By harnessing the power of statistical analysis and pattern recognition, machine learning algorithms can extract valuable insights from various data sources, including sound samples. As of July 5, 2023, there had been 767,726,861 confirmed COVID-19 cases reported to WHO, with 6,948,764 deaths [1]. The main symptoms of covid-19, according to the WHO, are a dry cough, difficulty breathing, and chest pain.