Abderraouf Ben Salem

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In this paper, a robust perceptual audio hashing system is presented. A model of the human auditory system is used to extract robust features from the outputs of a non-linear filter bank that mimics the human basilar membrane. Experiments on various audio excerpts show that this new ear-based front-end processing provides very effective hash values. The(More)
This paper deals with blind speech separation of instantaneous and convolutive mixtures of non-Gaussian sources. The separation criterion is based on higher order statistics (HOS) on the assumption that the sources are statistically independent. We propose to simplify and to improve the classical Herault-Jutten algorithm by choosing adequate high order(More)
We present a new subband decomposition method for the separation of convolutive mixtures of speech. This method uses a sample-by-sample algorithm to perform the subband decomposition by mimicking the processing performed by the human ear. The unknown source signals are separated by maximizing the entropy of a transformed set of signal mixtures through the(More)
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