Automated Audio Detection, Segmentation and Indexing, with Application to Post-Production Editing
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.
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