In this paper we focus on an audio segmentation. We present a novel method for robust estimation of decision-thresholds for accurate detection of acoustic change points in continuous audio streams. In standard segmentation procedures the decisionthresholds are usually set in advance and need to be tuned from development data. In the presented approach we tried to remove a need for using pre-determined decision-thresholds and propose a method for estimation of thresholds directly from the currently processed audio data. It employs change-detection methods from two well-established audio segmentation approaches based on the Bayesian Information Criterion. Following from that, we develop two audio segmentation procedures, which enable us to adaptively tune boundary-detection thresholds and to combine different audio representations in the segmentation process. The proposed segmentation procedures are tested on broadcast news audio data.
Bibliographic reference. Žibert, Janez / Brodnik, Andrej / Mihelič, France (2009): "An adaptive BIC approach for robust audio stream segmentation", In INTERSPEECH-2009, 2539-2542.