The soundscape dynamics of human agglomeration

TL;DR

This paper analyzes the soundscape dynamics during human gatherings, revealing complex statistical properties such as heavy tails, long-range correlations, and validating a GARCH model to describe these phenomena.

Contribution

It provides a novel statistical characterization of human agglomeration soundscapes and demonstrates the applicability of a GARCH model to capture their dynamics.

Findings

Heavy tail distributions in sound amplitudes

Long-range correlations in sound intensity

GARCH model fits the observed data well

Abstract

We report a statistical analysis about people agglomeration soundscape. Specifically, we investigate the normalized sound amplitudes and intensities that emerge from people collective meetings. Our findings support the existence of nontrivial dynamics characterized by heavy tail distributions in the sound amplitudes, long-range correlations in the sound intensity and non-exponential distributions in the return interval distributions. Additionally, motivated by the time-dependent behavior present in the volatility/variance series, we compare the observational data with those obtained from a minimalist autoregressive stochastic model, a GARCH process, finding a good agreement.