This paper presents an effective method for improving the performance of speaker identification system based on the multiresolution properly of the wavelet transform, the input speech signal is decomposed into L subbands. To capture the characteristic of the vocal tract, the liner prediction code of each band (including the linear predictive code (LPC)for full band) are calculated.
The feature recombination schemes combines the LPC of each band and LPC for full band in single feature vector then the Euclidean distance measure is used to perform the similarity measure between the test and reference speech. Experimental results shows that the proposed method achieve better performance than speaker identification using LPC and real cepstral coefficients.