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This paper presents an experimental implementation of a low-complexity speaker recognition algorithm working in the compressed speech domain. The goal is to perform speaker modeling and identication without decoding the speech bitstream to extract speaker dependent features, thus saving important system resources, for instance, in mobile devices. The compressed bitstream values of the widely used GSM AMR speech coding standard are studied to identify statistics enabling fair recognition after adoi:10.1109/icme.2005.1521510 dblp:conf/icmcs/PetraccaSM05 fatcat:lhjqpvlkzzeg7kfeg423dvduzu