The current work deals with audio event detection, segmentation and characterization, in order to be further utilized in post-production. Browsing, selection and characterization of audio-visual content is a tiresome task, especially in audio / video editing applications, where an enormous amount of recordings with different characteristics is usually involved. Automated detection, segmentation and general audio classification are essential to deploy flexible and effective audio-visual content management. A multi-resolution scanning procedure, based mainly in wavelet-processing, is currently proposed where various energy-based comparators and signal-complexity metrics have been tested for detection purposes. A variety of audio features, including MPEG-7 audio low level descriptors, have been considered for events’ characterization and indexing purposes. Extraction of the detection / characterization results via MPEG-7 description schemes or similar indexing files are considered.
Authors:
Avdelidis, Kostantinos A.; Dimoulas, Charalampos A.; Kalliris, George M.; Papanikolaou, George V.; Vegiris, Christos
Affiliations:
Lab of Electroacoustics, Aristotle University of Thessaloniki; Laboratory of Electronic Media, Aristotle University of Thessaloniki(See document for exact affiliation information.)
AES Convention:
122 (May 2007)
Paper Number:
7138
Publication Date:
May 1, 2007
Subject:
Audio-Video Systems
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