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Three different classification solutions for distinguishing events from non-events in surveillance audio are described and evaluated. The three compared methods are energy functions, Gaussian mixture modelling algorithms (GMM) and existing voice activity detectors (VAD). Recorded test signals with corresponding manually labelled ground truth files are used to determine the accuracies of the method
