Audio fingerprinting based on normalized spectral subband moments

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The performance of a fingerprinting system, which is often measured in terms of reliability and robustness, is directly related to the features that the system uses. In this letter, we present a new audio-fingerprinting method based on the normalized spectral subband moments. A threshold used to reliably determine a fingerprint match is obtained by modeling the features as a stationary process. The robustness of the normalized moments was evaluated experimentally and compared with that of the spectral flatness measure. Among the considered subband features, the first-order normalized moment showed the best performance for fingerprinting.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2006-04
Language
English
Article Type
Article
Citation

IEEE SIGNAL PROCESSING LETTERS, v.13, no.4, pp.209 - 212

ISSN
1070-9908
DOI
10.1109/LSP.2005.863678
URI
http://hdl.handle.net/10203/92208
Appears in Collection
EE-Journal Papers(저널논문)
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