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A Robust Speaker Identification System

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A Robust Speaker Identification System

Zaw Win Aung


Zaw Win Aung "A Robust Speaker Identification System" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-2 | Issue-5, August 2018, pp.2057-2064, URL: https://www.ijtsrd.com/papers/ijtsrd18274.pdf

This paper is aimed to implement a robust speaker identification system. It is a software architecture which identifies the current talker out of a set of speakers. The system is emphasized on text-dependent speaker identification system. It contains three main modules: endpoint detection, feature extraction and feature matching. The additional module, endpoint detection, removes unwanted signal and background noise from the input speech signal before subsequent processing. In the proposed system, Short-Term Energy analysis is used for endpoint detection. Mel-frequency Cepstrum Coefficients (MFCC) is applied for feature extraction to extract a small amount of data from the voice signal that can later be used to represent each speaker. For feature matching, Vector Quantization (VQ) approach using Linde, Buzo and Gray (LBG) clustering algorithm is proposed because it can reduce the amount of data and complexity. The experimental study shows that the proposed system is more robust than using the original system and it is faster in computation than the existing one. To implement this system MATLAB is used for programming.

speaker recognition; speaker identification; endpoint detection; mel-frequency cepstrum coefficients; vector quantization

Volume-2 | Issue-5, August 2018
IJTSRD | www.ijtsrd.com | E-ISSN 2456-6470
Copyright © 2019 by author(s) and International Journal of Trend in Scientific Research and Development Journal. This is an Open Access article distributed under the terms of the Creative Commons Attribution License (CC BY 4.0) (http://creativecommons.org/licenses/by/4.0)

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