Training audio events detectors with a sound effects corpus

This paper describes the work done in the framework of the VIDIVIDEO European project in terms of audio event detection. Our first experiments concerned the detection of nonvoice sounds, such as birds, machines, traffic, water and steps. Given the unavailability of a corpus labelled in terms of audio events, we used a relatively small sound effect corpus for training. Our initial experiments with one-against-all SVM classifiers for these 5 classes showed us the feasibility of using this type of data for training, thus avoiding the extremely morose task of manual labelling of a very high number of audio events. Preliminary integration experiments are quite promising.