Abstract
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 proposed audio hashing system performs very satisfactorily in identification and it turned out very resilient to a large variety of severe audio attacks.