Development of automatic speaker identification system

A general method for text-independent speaker identification system using discrete wavelet transform (DWT) is presented. The production of identification is based on a predefined threshold in conjunction with a subset mother wavelet properly selected to extract the speaker´s features. The classification process to produce the speakers codebooks is achieved by using the vector quantization technique (VQ) with a proper algorithm to minimize the time needed to create the data vector. The performance of the proposed system is demonstrated by considering two databases; 28 persons (males and females of 7 different regions) from the international TIMIT database down-sampled to 8 kHz and a group of 5 local females recorded in a semiquiet environment. TIMIT results of text-independent identification indicates 85.7% for speakers of same region and 90.5% for speakers of different regions whereas 88% and 100% identification for the local group are obtained. However, the proposed method shows 100% successful text-dependent recognition for both database of speakers.