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Reseach Article

Text-Independent Speaker Recognition for Low SNR Environments with Encryption

by Aman Chadha, Divya Jyoti, M. Mani Roja
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 31 - Number 10
Year of Publication: 2011
Authors: Aman Chadha, Divya Jyoti, M. Mani Roja

Aman Chadha, Divya Jyoti, M. Mani Roja . Text-Independent Speaker Recognition for Low SNR Environments with Encryption. International Journal of Computer Applications. 31, 10 ( October 2011), 43-50. DOI=10.5120/3864-5398

@article{ 10.5120/3864-5398,
author = { Aman Chadha, Divya Jyoti, M. Mani Roja },
title = { Text-Independent Speaker Recognition for Low SNR Environments with Encryption },
journal = { International Journal of Computer Applications },
issue_date = { October 2011 },
volume = { 31 },
number = { 10 },
month = { October },
year = { 2011 },
issn = { 0975-8887 },
pages = { 43-50 },
numpages = {9},
url = { },
doi = { 10.5120/3864-5398 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
%0 Journal Article
%1 2024-02-06T20:17:50.984452+05:30
%A Aman Chadha
%A Divya Jyoti
%A M. Mani Roja
%T Text-Independent Speaker Recognition for Low SNR Environments with Encryption
%J International Journal of Computer Applications
%@ 0975-8887
%V 31
%N 10
%P 43-50
%D 2011
%I Foundation of Computer Science (FCS), NY, USA

Recognition systems are commonly designed to authenticate users at the access control levels of a system. A number of voice recognition methods have been developed using a pitch estimation process which are very vulnerable in low Signal to Noise Ratio (SNR) environments thus, these programs fail to provide the desired level of accuracy and robustness. Also, most text independent speaker recognition programs are incapable of coping with unauthorized attempts to gain access by tampering with the samples or reference database. The proposed text-independent voice recognition system makes use of multilevel cryptography to preserve data integrity while in transit or storage. Encryption and decryption follow a transform based approach layered with pseudorandom noise addition whereas for pitch detection, a modified version of the autocorrelation pitch extraction algorithm is used. The experimental results show that the proposed algorithm can decrypt the signal under test with exponentially reducing Mean Square Error over an increasing range of SNR. Further, it outperforms the conventional algorithms in actual identification tasks even in noisy environments. The recognition rate thus obtained using the proposed method is compared with other conventional methods used for speaker identification.

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Index Terms

Computer Science
Information Sciences


Speaker Individuality Text-independence Pitch Extraction Voice Recognition Autocorrelation