Sound classification can be a hard task, especially when sound samples have small variations that can be imperceptible to the human ear. The use of machines, and recently machine learning models, has been shown to be an effective approach to solving the problem of classifying sounds. These applications can help improve diagnoses and have been a topic of research in areas such as cardiology and pulmonology. Recent innovations such as a convolutional neural network identifying COVID-19 coughs and the MIT AI model detecting asymptomatic COVID-19 infections using cough recordings show some promising results for identifying COVID-19 patients just by the sound of their coughs. Looking at these references, this task may look quite challenging and like something that can be done only by top-notch researchers. In this post, we will discuss how you can get very promising results using the machine learning and audio functionalities in the Wolfram Language.