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Multi Lingual Speaker Identification on Foreign Languages using Artificial Neural Network

by Prateek Agrawal, Harjeet Kaur, Gurpreet Kaur
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 57 - Number 13
Year of Publication: 2012
Authors: Prateek Agrawal, Harjeet Kaur, Gurpreet Kaur
10.5120/9177-3584

Prateek Agrawal, Harjeet Kaur, Gurpreet Kaur . Multi Lingual Speaker Identification on Foreign Languages using Artificial Neural Network. International Journal of Computer Applications. 57, 13 ( November 2012), 36-42. DOI=10.5120/9177-3584

@article{ 10.5120/9177-3584,
author = { Prateek Agrawal, Harjeet Kaur, Gurpreet Kaur },
title = { Multi Lingual Speaker Identification on Foreign Languages using Artificial Neural Network },
journal = { International Journal of Computer Applications },
issue_date = { November 2012 },
volume = { 57 },
number = { 13 },
month = { November },
year = { 2012 },
issn = { 0975-8887 },
pages = { 36-42 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume57/number13/9177-3584/ },
doi = { 10.5120/9177-3584 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:01:21.323837+05:30
%A Prateek Agrawal
%A Harjeet Kaur
%A Gurpreet Kaur
%T Multi Lingual Speaker Identification on Foreign Languages using Artificial Neural Network
%J International Journal of Computer Applications
%@ 0975-8887
%V 57
%N 13
%P 36-42
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Based on the Back Propagation Algorithm, this paper portrait a method for speaker identification in multiple foreign languages. In order to identify speaker, the complete process goes through recording of the speech utterances of different speakers in multiple foreign languages, features extraction, data clustering and system training. In order to realize the purpose, a database has been prepared which contains one sentence in 8 different international languages i. e. Catalan, French, Finnish, Italian, Portuguese, Indonesian, Hindi, English spoken by 19 distinct speakers, both male and female, in each language. With total size of 760 speech utterances, the average performance of the system is 95. 657%. Application of developed system is mainly used in speaker authentication in telephony security oriented applications where the normal conversations are of short durations and the tendency of the spokesperson is to switch language from one to another

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Index Terms

Computer Science
Information Sciences

Keywords

Artificial Neural Network (ANN) Back Propagation Algorithm (BPA) Cepstral Analysis Multilingual Speaker Recognition Power Spectral Density (PSD)

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