The Covid-19 pandemic has been a scourge upon humanity, claiming the lives of more than 5 million people worldwide. Although vaccines are being distributed worldwide, there is an apparent need for affordable screening techniques to serve parts of the world that do not have access to traditional medicine. Artificial Intelligence can provide a solution utilizing cough sounds as the primary screening mode. This paper presents multiple models that have achieved relatively respectable perfor mance on the largest evaluation dataset currently presented in academic literature. Moreover, we also show that performance increases with training data size, showing the need for the world wide collection of data to help combat the Covid-19 pandemic with non-traditional means.

翻译：Covid-19大流行病是人类的灾祸,夺去了全世界500多万人的生命,虽然疫苗正在全世界分发,但显然需要负担得起的筛选技术,为世界上无法获得传统医学的地区服务,人工智能可以用咳嗽声音作为主要筛选模式提供解决办法,本文介绍了在目前学术文献中提供的最大评价数据集方面相对可敬的多模式,此外,我们还表明,由于培训数据规模较大,绩效有所提高,表明需要在全世界广泛收集数据,帮助用非传统手段防治Covid-19大流行病。