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

Avdelidis KA, Dimoulas CA, Kalliris GM, Papanikolaou GV, Vegiris C. Automated Audio Detection, Segmentation and Indexing, with Application to Post-Production Editing. In: AES Convention 122. Audio Engineering Society; 2007. Paper 7138. Available from: https://aes.org/publications/elibrary-page/?id=14123

@inproceedings{Avdelidis2007_14123,
  author = {Avdelidis, Kostantinos A. and Dimoulas, Charalampos A. and Kalliris, George M. and Papanikolaou, George V. and Vegiris, Christos},
  title = {{Automated Audio Detection, Segmentation and Indexing, with Application to Post-Production Editing}},
  booktitle = {AES Convention 122},
  note = {Paper 7138},
  year = {2007},
  month = may,
  publisher = {Audio Engineering Society},
  url = {https://aes.org/publications/elibrary-page/?id=14123}
}

TY  - CPAPER
TI  - Automated Audio Detection, Segmentation and Indexing, with Application to Post-Production Editing
AU  - Avdelidis, Kostantinos A.
AU  - Dimoulas, Charalampos A.
AU  - Kalliris, George M.
AU  - Papanikolaou, George V.
AU  - Vegiris, Christos
T2  - AES Convention 122
M1  - Paper 7138
PY  - 2007
DA  - 2007/05/06
UR  - https://aes.org/publications/elibrary-page/?id=14123
PB  - Audio Engineering Society
LA  - en
AB  - 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.
ER  -