Speech Watermarking through Parametric Modeling

Abstract

A general formulation for speech watermarking through parametric modeling is suggested, then the paper focuses on a watermarking technique based on linear-predictive (LP) modeling of speech. In the particular strategy employed here, information is embedded by modifying the autocorrelation values of the original speech. The amount of information that can be embedded is subject to fidelity constraints. The modified LP coe#cients derived from the new set of autocorrelation values are used for reconstructing the watermarked speech. The perceptual quality of the watermarked speech depends on the relative energy of the embedded watermark, the watermark sequence used, and the LP model order. Robustness of the technique to various signal processing operations and attacks like compression, cropping, and additive noise are studied via experiments on a small speech application. Factors a#ecting watermark robustness and related security issues are also discussed