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Text Independent Language Recognition using Dhmm

by M. Sadanandam, V. Kamakshi Prasad, V. Janaki
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 48 - Number 7
Year of Publication: 2012
Authors: M. Sadanandam, V. Kamakshi Prasad, V. Janaki
10.5120/7364-0208

M. Sadanandam, V. Kamakshi Prasad, V. Janaki . Text Independent Language Recognition using Dhmm. International Journal of Computer Applications. 48, 7 ( June 2012), 42-45. DOI=10.5120/7364-0208

@article{ 10.5120/7364-0208,
author = { M. Sadanandam, V. Kamakshi Prasad, V. Janaki },
title = { Text Independent Language Recognition using Dhmm },
journal = { International Journal of Computer Applications },
issue_date = { June 2012 },
volume = { 48 },
number = { 7 },
month = { June },
year = { 2012 },
issn = { 0975-8887 },
pages = { 42-45 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume48/number7/7364-0208/ },
doi = { 10.5120/7364-0208 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:43:30.806641+05:30
%A M. Sadanandam
%A V. Kamakshi Prasad
%A V. Janaki
%T Text Independent Language Recognition using Dhmm
%J International Journal of Computer Applications
%@ 0975-8887
%V 48
%N 7
%P 42-45
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Spoken Language Identification is a task of recognizing the language from an unknown utterance of speech. The ability of machines to distinguish between different languages becomes an important concern with the emerging trends in global communications which are multilingual nature. This paper describes a text independent language recognition system using a common code book and discrete hidden Markov models (DHMM) to achieve a very good LID recognition performance with less computation time comparing with that of a state of art phone based systems available in literature. This approach includes generation of a common codebook and training of DHMM, one for each language. The experiments are carried out on the database of Indian language consists of six languages namely Telugu, Tamil, Hindi, Marathi, Malayalam and Kannada.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Language Identification (lid) Mel Frequency Cepstral Coefficients (mfcc) Vector Quantization (vq) Discrete Hidden Markov Model (dhmm)

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