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Audio fingerprinting based on normalized spectral subband moments

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6 Author(s)
J. S. Seo ; Dept. of Electr. Eng. & Comput. Sci., Korea Adv. Inst. of Sci. & Technol., Daejeon, South Korea ; Minho Jin ; Sunil Lee ; Dalwon Jang
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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.

Published in:

IEEE Signal Processing Letters  (Volume:13 ,  Issue: 4 )