On Room Mode Analysis for Classifying Indoor Events Using Loudspeaker and AI

Abstract

Room modes are known to alter the low frequency response of electrodynamic loudspeakers and are one of the biggest obstacles to accurate sound reproduction in listening rooms. The characteristics of the room may therefore influence the response of the loudspeaker at low frequencies due of the strong modal acoustic coupling. In this presentation, we show how to take advantage of this interaction to detect changes occurring in the room from the loudspeaker impedance. We present a practical methodology that combines electroacoustics and AI to track changes in the modal frequency response of the room related to the presence of people, the opening of doors and windows or a temperature shift. The performance and limitations of the concept are illustrated using calculated data and measurements taken in a real room