Text-independent Speaker Identification System Using Average Pitch and Formant Analysis

The aim of this paper is to design a closed-set text-independent Speaker Identification system using average pitch and speech features from formant analysis. The speech features represented by the speech signal are potentially characterized by formant analysis (Power Spectral Density). In this paper we have designed two methods: one for average pitch estimation based on Autocorrelation and other for formant analysis. The average pitches of speech signals are calculated and employed with formant analysis. From the performance comparison of the proposed method with some of the existing methods, it is evident that the designed speaker identification system with the proposed method is superior to others.