Pairwise boosted audio fingerprint

Authors:
Dalwon Jang;Chang D. Yoo;Sunil Lee;Sungwoong Kim;Ton Kalker
Affiliations:
Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea;Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea;Multimedia Platform Laboratory, Digital Media and Communications R&D Center, Samsung Electronics, Suwon, Korea;Department of Electrical Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Korea;Hewlett-Packard Laboratories, Multimedia Communications and Networking Laboratory, Palo Alto, CA
Venue:
IEEE Transactions on Information Forensics and Security - Special issue on electronic voting
Year:
2009

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Abstract

A novel binary audio fingerprint obtained by filtering and then quantizing the spectral centroids is proposed. A feature selection algorithm, coined pairwise boosting (PB), is used to determine the filters and quantizers by casting the fingerprinting problem of identifying a query audio clip into a binary classification problem. The PB algorithm selects the filters and quantizers which lead to accurate classification of matching and nonmatching audio pairs: a matching pair is an audio pair that should be classified as being identical, and a nonmatching pair is a pair that should be classified as being different. By iteratively reducing the classification error of both matching and nonmatching pairs, the PB algorithm improves both the robustness and discriminating ability. In our experiments, the proposed fingerprint outperformed previously reported binary fingerprints in terms of robustness and discriminating ability. In the experiment, we compared the performances of a number of distance measures.