  In this paper, a novel method of designing a codebook for noise robust
speaker identification purpose utilizing Genetic Algorithm has been proposed.
Wiener filter has been used to remove the background noises from the source
speech utterances. Speech features have been extracted using standard speech
parameterization method such as LPC, LPCC, RCC, MFCC, (delta)MFCC and
(delta)(delta) MFCC. For each of these techniques, the performance of the
proposed system has been compared. In this codebook design method, Genetic
Algorithm has the capability of getting global optimal result and hence
improves the quality of the codebook. Comparing with the NOIZEOUS speech
database, the experimental result shows that 79.62 percent accuracy has been
achieved.
