Abstract

The COVID-19 pandemic had an unprecedented effect in human activity and city landscapes. A very notorious transformation during this period was the change in noise levels and patterns across cities. Small scale studies have show this change in noise levels across different locations in the globe. In this work, we extend these studies by using historical audio data from the SONYC sensor network deployed in New York City. We exploit machine listening models to understand not only noise levels but also patterns, by performing a sound source presence analysis. Finally, we contrast our finding from the acoustic data with noise complaints to better understand the relationship between noise and our perception of it.

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