In this paper a method of text-independent speaker recognition using discrete vector quantization is presented. The identification
experiments were performed in a closed set of 599 speakers and two various types of features were tested: cepstral mean subtraction coeficients
and mel-frequency cepstral coeficients. The effect of the various codebook size on the speaker identification performance was investigated
