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In most real-world audio recordings, we encounter several types of audio events. In this paper, we develop a technique for detecting signature audio events, that is based on identifying patterns of occurrences of automatically learned atomic units of sound, which we call Acoustic Unit Descriptors or AUDs. Experiments show that the methodology works as well for detection of individual events and their boundaries in complex recordings.doi:10.1109/icassp.2012.6287923 dblp:conf/icassp/KumarDSCR12 fatcat:myzzngdyarfctoja7j3ze5gena