Pairwise Boosted Audio Fingerprint

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.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2009-12
Language
ENG
Citation

IEEE TRANSACTIONS ON INFORMATION FORENSICS AND SECURITY, v.4, no.4, pp.995 - 1004

ISSN
1556-6013
DOI
10.1109/TIFS.2009.2034452
URI
http://hdl.handle.net/10203/100398
Appears in Collection
EE-Journal Papers(저널논문)
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