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Audio-Visual Feature Extraction for Semi-Automatic Annotation of Meetings

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19 out of 47 users found this white paper useful


Publisher Graz University of Technology
Publisher Registration N/A
Topics Multimedia, Software Engineering Date added 07 Jul 2006
Downloads 13 Format 261.3KB PDF

This paper presents the building blocks of the semi-automatic annotation tool which supports multi-modal and multi-level annotation of meetings. The main focus is on the proper design and functionality of the modules for recognizing meeting actions. The key features, identity and position of the speakers, are provided by different modalities (audio and video). Three audio algorithms (Voice Activity Detection, Speaker Identification and Direction of Arrival) and three video algorithms (Detection, Tracking and Identification) form the low-level feature extraction components. Low-level features are automatically merged and the recognized actions are proposed to the user by visualizing them. The annotation labels are related but not limited to events during meetings.

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19 out of 47 users found this white paper useful


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