NDLI: A Hybrid Reliable Algorithm for Speaker Recognition Based on Improved DTW and VQ by Genetic Algorithm in Noisy Environment

Content Provider	IEEE Xplore Digital Library
Author	Fallahzadeh, Mohammad Reza Farokhi, Fardad Izadian, Mahboobeh Berangi, Ali Akbar
Copyright Year	2011
Abstract	in this paper a hybrid reliable algorithm is presented which used DTW and VQ optimization plan based on genetic algorithm for text dependent and text independent speaker identification in noisy environment. After preprocessing and feature extraction, to remove the effect of microphone type on saved data, the Cepstral Mean Subtraction (CMS) coefficients have been used. Dynamic Time Warping (DTW) and Vector Quantization (VQ) have been used with Linear Predictive Cepstral Coefficients (LPCC), ÄLPCC, ÄÄLPCC, CMS and Mel Frequency Cepstral Coefficients (MFCC), ÄMFCC, ÄÄMFC, CMS respectively. The Linde-Buzo-Grey (LBG) algorithm has been used to calculate the code book of speakers. Finally genetic algorithm (GA) has been used for optimization and enhancement. The algorithm found optimum coefficients as weights in DTW and calculate best centroids (code books) in VQ algorithm as well. The performance of the algorithm was evaluated by using 25 speakers (15 male and 10 female) for training and testing in noisy and normal condition and experimental results was shown that 0% identification Error Rate was achieved.
Starting Page	269
Ending Page	273
File Size	328925
Page Count	5
File Format	PDF
ISBN	9781612843148
e-ISBN	9781612843148
DOI	10.1109/CMSP.2011.143
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-05-14
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Vector Quantization (VQ) Robust Speaker identification Heuristic algorithms Noisy environment Dynamic Time Warping (DTW) Speech recognition Feature extraction Genetic Algorithm (GA) Speaker recognition Noise measurement Mel frequency cepstral coefficient Genetic algorithms
Content Type	Text
Resource Type	Article

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