This paper is concerned with speaker identification problem. The identification is carried out comparing feature vectors extracted from pseudostationary parts of speech utterances. Both likelihood ratio and cepstral distances are used for comparing feature vectors. The identification approach is suitable for text-dependent and text-independent identification.
Keywords: likelihood ratio distance, cepstral distance, pseudostationary segments