Audio Events Detection in Public Transport Vehicle

International audience; This paper addresses the problem of automatic audio analysis for aided surveillance application in public transport. The aim of such application is to detect critical situations and to warn the control room. We propose a comparative study of two methods of modelisation/classification of acoustical segments. The problem is quite similar to the "'audio indexing"' framework, nevertheless the environment here is very noisy. We present two general frameworks based on Gaussian Model Mixture (GMM) and Support Vector Machine (SVM) to achieve shout detection in railway embedded environment.