Roopalakshmi, R.Ram Mohana Reddy, Guddeti2020-03-302020-03-3020112011 IEEE 5th International Conference on Internet Multimedia Systems Architecture and Application, IMSAA 2011 - Conference Proceedings, 2011, Vol., , pp.-https://idr.nitk.ac.in/jspui/handle/123456789/6825Acoustic features are robust and powerful in video description, but not fully exploited for the emerging Content-Based video Copy Detection (CBCD) methods. To solve this discrepancy, this paper proposes a new CBCD approach using audio spectral features compared to existing visual content based methods. The proposed method incorporates three stages: 1) Extraction of spectral descriptors including centroid and energy; 2) Integration of resultant features to compute highly informative spectral descriptive words; 3) Utilization of clustering approach to speed up the similarity matching process. The results tested on TRECVID-2008 dataset, demonstrate the improved detection accuracy of proposed method (up to 27.845%) compared to reference methods against various transformations such as fast forward, slow motion, mp3 compression, and multiband companding. � 2011 IEEE.Book chapter