Abstract:
In this paper, an improved strategy for
automated text based speaker identification scheme
has been proposed. The identification process
incorporates the Hidden Markov Model technique.
After preprocessing the speech, HMM is used in the
learning and identification. Features are extracted
by different techniques such as RCC, MFCC,
ÄMFCC, ÄÄMFCC, LPC and LPCC which is
almost different in each case. The highest
identification rate of 93% has been achieved in the
close set text dependent speaker identification
system.
