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The analysis of three sets of feature vectors used in speaker identification (ID) systems for speech signals received in encoding-decoding process with AMR, SPEEX and MELP coders has been presented. We have analyzed feature sets for various speech coding bit rates using SVM-based speaker ID system. The results were compared with identification accuracy obtained with vectors where fundamental frequency was an additional feature. Performed experiments show that such feature contributes better identification accuracy for coded speech than uncoded one in most cases.