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Speech Recognition System For North-East Indian Accent

by Moirangthem Tiken Singh, Abdur Razzaq Fayjie, Biswajeet Kachari
journal cover thumbnail

International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 9 - Number 4
Year of Publication: 2015
Authors: Moirangthem Tiken Singh, Abdur Razzaq Fayjie, Biswajeet Kachari
10.5120/ijais15-451398

Moirangthem Tiken Singh, Abdur Razzaq Fayjie, Biswajeet Kachari . Speech Recognition System For North-East Indian Accent. International Journal of Applied Information Systems. 9, 4 ( July 2015), 1-9. DOI=10.5120/ijais15-451398

@article{ 10.5120/ijais15-451398,
author = { Moirangthem Tiken Singh, Abdur Razzaq Fayjie, Biswajeet Kachari },
title = { Speech Recognition System For North-East Indian Accent },
journal = { International Journal of Applied Information Systems },
issue_date = { July 2015 },
volume = { 9 },
number = { 4 },
month = { July },
year = { 2015 },
issn = { 2249-0868 },
pages = { 1-9 },
numpages = {9},
url = { https://www.ijais.org/archives/volume9/number4/766-1398/ },
doi = { 10.5120/ijais15-451398 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T18:59:58.167282+05:30
%A Moirangthem Tiken Singh
%A Abdur Razzaq Fayjie
%A Biswajeet Kachari
%T Speech Recognition System For North-East Indian Accent
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 9
%N 4
%P 1-9
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Speech recognition is the process of converting an acoustic waveform into the text containing the similar information conveyed by the speaker. This paper presents a speech recognition system for English digits in Indian (especially North Eastern) accent. Hidden Markov Model Tool kit (HTK-3. 4. 1) is chosen to implement the Hidden Markov Model as classifier with several set of Hidden Markov Model mixture. Mel Frequency Cepstral Coefficients are used as speech features. Experiments were performed for data collected in natural noise environment. The performance is evaluated using recognition rate. Hidden Markov Model state numbers and number of mixtures are investigated and possible directions for future research work are suggested.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Regional accent HMM HMM mixture MFCC

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