PERFORMANCE OF PHILIPS AUDIO FINGERPRINTING UNDER ADDITIVE NOISE

摘要

We present a theoretical analysis of the Philips audio fingerprinting method under Gaussian white noise distortion for correlated stationary Gaussian sources. Prior analyses were for white Gaussian sources, which do not model realistically real audio signals. Our approach relies on formulating the unquantized fingerprint as a quadratic form, which affords a systematic way to compute the model parameters. We provide closed-form analytical upper bounds for the probability of bit error of the hash, and we apply these expressions to real audio signals.