A classification method for crowded situation using environmental sounds based on Gaussian mixture model-universal background model

This paper presents a method to classify a situation of being crowded with people using environmental sounds that are collected by smartphones. A final goal of the research is to estimate “crowd-density” using only environmental sounds collect by smartphones. Advantages of the approach are (1) acoustic singles can be collected and processed at low cost, (2) because many people carry smartphones, crowd-density can be obtained not only from many places, but also at any time. As the first step, in this paper, we tried to classify “a situation of being crowded with people.” We collected environmental sounds using smartphones both in residential area and downtown area. The total duration of the collected data is 77,900 seconds. The sound of “crowded with people” is defined as buzz-buzz where more than one person talked at the same time. Two kinds of classifiers were trained on the basis of the GMM-UBM (Gaussian Mixture Model and Universal Background Model) method. The one was trained with acoustic features tha...