Volume 5, Number 4 (2020)
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Home > Journals > SCIREA Journal of Electrical Engineering > Archive > Paper Information

MFCC based performance analysis of VQ and GMM Speaker identification system

Volume 5, Issue 4, August 2020    |    PP. 89-99    |PDF (407 K)|    Pub. Date: August 12, 2020
11 Downloads     171 Views  

Author(s)
Chandar Kumar, Faculty of Engineering, Science and Technology, Indus University, Karachi, Sindh, Pakistan
Dr.Engr.Zahid Ali, Faculty of Engineering, Science and Technology, Indus University, Karachi, Sindh, Pakistan
Suresh Kumar, Faculty of Engineering, Science and Technology, Indus University, Karachi, Sindh, Pakistan
Syed Zain ul Abedin Abid, Faculty of Engineering, Science and Technology, Indus University, Karachi, Sindh, Pakistan
Chaman Lal, Faculty of Engineering, Science and Technology, Indus University, Karachi, Sindh, Pakistan

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. Vol. 5 , No. 4 , 2020 , pp. 89 - 99 .

References

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