The ultimate goal of this study is to gain a better understanding of the affective state of mice, by analyzing mouse vocalizations. To achieve this goal, this study aimed to distinguish vocalizations from recordings using an artificial neural network. In order to analyze these calls, they must first be identified and characterized. While human technicians are very accurate at these classifications, manually annotating the ultrasonic vocalizations (USVs) is a time-intensive process and might be better if it were automated. This project relies on neural networks, a machine learning technique that employs weighted inputs with the ability to learn as a method of discerning calls from noise.