On the Detection of Multiplicative Watermarks for Speech Signals in the Wavelet and DCT Domains
Blind multiplicative watermarking schemes for speech signals using wavelets and discrete cosine transform are presented. Watermarked signals are modeled using a generalized Gaussian distribution (GGD) and Cauchy probability model. Detectors are developed employing generalized likelihood ratio test (GLRT) and locally most powerful (LMP) approach. The LMP scheme is used for the Cauchy distribution, while the GLRT estimates the gain factor as an unknown parameter in the GGD model. The detectors are tested using Monte Carlo simulation and results show the superiority of the proposed LMP/Cauchy detector in some experiments