Giving access to the semantically rich content of large amounts of digital audiovisual data using an automatic and generic method is still an important challenge. The aim of our work is to address this issue while focusing on temporal aspects. Our approach is based on a method previously developed for analyzing temporal relations from a data mining point of view. This method is used to detect zones of a document in which two characteristics are active. These characteristics can result from low-level segmentations of the audio or video components, or from more semantic processings. Once "activity zones" have been detected, we propose to compute a set of additional descriptors in order to better characterize them. The method is applied in the scope of the EPAC project that focuses on the detection and the characterization of conversational speech.
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