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Analysis of Different Feature for Language Identification

by Snehal V. Gite, J. V. Shinde
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 146 - Number 10
Year of Publication: 2016
Authors: Snehal V. Gite, J. V. Shinde
10.5120/ijca2016910924

Snehal V. Gite, J. V. Shinde . Analysis of Different Feature for Language Identification. International Journal of Computer Applications. 146, 10 ( Jul 2016), 10-14. DOI=10.5120/ijca2016910924

@article{ 10.5120/ijca2016910924,
author = { Snehal V. Gite, J. V. Shinde },
title = { Analysis of Different Feature for Language Identification },
journal = { International Journal of Computer Applications },
issue_date = { Jul 2016 },
volume = { 146 },
number = { 10 },
month = { Jul },
year = { 2016 },
issn = { 0975-8887 },
pages = { 10-14 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume146/number10/25433-2016910924/ },
doi = { 10.5120/ijca2016910924 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:50:03.406913+05:30
%A Snehal V. Gite
%A J. V. Shinde
%T Analysis of Different Feature for Language Identification
%J International Journal of Computer Applications
%@ 0975-8887
%V 146
%N 10
%P 10-14
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Language Identification is the task of identifying language spoken from unknown user. The main objective is to achieve accurate results in shortest speech segments by using automatic Language Identification system. It works on language classification that involves new language rapid learning identities and reduce the computational complexity. MFCC, GFCC, PLP and the combination of these feature are consider in language identification system. The proposed approach that transforms the spoken words to a represent low dimensional i-vector, on which classification techniques are applied. Feature extraction is done on input audio, Universal background model and i-vector extraction are used in proposed system in order to meet the challenges involved in rapidly making reliable decisions about the spoken language such as Marathi, Hindi and English. For the relevant languages under the different acoustic condition are used to capture robust feature extraction scheme.

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Index Terms

Computer Science
Information Sciences

Keywords

Language Identification Feature Extraction Universal background model.

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