Abstract
Speaker identification is the key area of digital signal processing where the synthesis and noise reduction of speech are the core research areas. Speaker identification system is influenced by the background noise which directly affects the efficiency of system and is still reflected as a challenging question in speaker identification system. Several useful techniques for feature extraction have been proposed and refined. In this paper, the performance of GMM and VQ has been investigated on the basis of their effects in text dependent speaker identification and proposed the optimum techniques for MFCC based speaker identification system.

Keywords
vector –quantization, speaker identification, Gaussian mixture

Cite this paper
Chandar Kumar, Dr.Engr.Zahid Ali, Suresh Kumar, Syed Zain ul Abedin Abid, Chaman Lal, MFCC based performance analysis of VQ and GMM Speaker identification system , SCIREA Journal of Electrical Engineering. Volume 5, Issue 4, August 2020 | PP. 89-99.

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