Introduction - If you have any usage issues, please Google them yourself
In this work, the Mel frequency Cepstrum Coefficient
(MFCC) feature has been used for designing a text
dependent speaker identification system. The extracted
speech features (MFCC’s) of a speaker are quantized to a
number of centroids using vector quantization algorithm.
These centroids constitute the codebook of that speaker.
MFCC’s are calculated in training phase and again in testing
phase. Speakers uttered same words once in a training
session and once in a testing session later. The Euclidean
distance between the MFCC’s of each speaker in training
phase to the centroids of individual speaker in testing phase
is measured and the speaker is identified according to the
minimum Euclidean distance. The code is developed in the
MATLAB environment and performs the identification
satisfactorily.