Research Article
Vector Quantization based Speaker Identification
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 4 - Issue 2 |
| Published: July 2010 |
| Authors: Jagdev Kaur, Reetkamal Kaur, Manjot Kaur Gill |
10.5120/806-1146
|
Jagdev Kaur, Reetkamal Kaur, Manjot Kaur Gill . Vector Quantization based Speaker Identification. International Journal of Computer Applications. 4, 2 (July 2010), 1-4. DOI=10.5120/806-1146
@article{ 10.5120/806-1146,
author = { Jagdev Kaur,Reetkamal Kaur,Manjot Kaur Gill },
title = { Vector Quantization based Speaker Identification },
journal = { International Journal of Computer Applications },
year = { 2010 },
volume = { 4 },
number = { 2 },
pages = { 1-4 },
doi = { 10.5120/806-1146 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2010
%A Jagdev Kaur
%A Reetkamal Kaur
%A Manjot Kaur Gill
%T Vector Quantization based Speaker Identification%T
%J International Journal of Computer Applications
%V 4
%N 2
%P 1-4
%R 10.5120/806-1146
%I Foundation of Computer Science (FCS), NY, USA
Abstract
The automatic speaker recognition technologies have developed into more and more important modern technologies required by many speech-aided applications. The main challenge for automatic speaker recognition is to deal with the variability of the environments and channels from where the speech was obtained. Speaker recognition system is a system which recognizes the speaker as opposed to what is being said by the speaker as in case of speech recognition. Speaker recognition technology makes it possible to the speaker's voice to control access to restricted services, for example, phone access to banking, database services, shopping or voice mail, and access to secure equipments. The main aim of this paper is speaker identification, which consists of comparing a speech signal from an unknown speaker to a database of known speakers. The methodology followed in this paper for Speaker identification is using Feature Extraction process and then Vector Quantization of extracted features is done using k-means algorithm. At last, the speaker is identified by comparing the data from a tested speaker to the database of each speaker and then measuring the difference.
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