Sonia Djaziri Larbi

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Identification and compensation purposes of nonlinear systems are of interest for many audio processing applications. The analysis of systems under test must be done through realistic audio inputs in order to capture different aspects of the nonlinearity. However, the Gaussianity of the tested signal, is a desirable factor because it guarantees easy(More)
In this paper, a new perceptual spread spectrum audio watermarking scheme is discussed. The watermark embedding process is performed in the Empirical Mode Decomposition (EMD) domain, and the hybrid watermark extraction process is based on the combination of EMD and ISA (Independent Subspace Analysis) techniques, followed by the generic detection system,(More)
Nonlinear audio system identification generally relies on Gaussianity, whiteness and stationarity hypothesis on the input signal, although audio signals are non-Gaussian, highly correlated and non-stationary. However, since the physical behavior of nonlinear audio systems is input-dependent, they should be identified using natural audio signals (speech or(More)