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Reseach Article

A Natural Human-Machine Interaction via an Efficient Speech Recognition System

by Shachi Sharma, Krishna Kumar Sharma, Himanshu Arora
International Journal of Applied Information Systems
Foundation of Computer Science (FCS), NY, USA
Volume 4 - Number 9
Year of Publication: 2012
Authors: Shachi Sharma, Krishna Kumar Sharma, Himanshu Arora
10.5120/ijais12-450797

Shachi Sharma, Krishna Kumar Sharma, Himanshu Arora . A Natural Human-Machine Interaction via an Efficient Speech Recognition System. International Journal of Applied Information Systems. 4, 9 ( December 2012), 31-37. DOI=10.5120/ijais12-450797

@article{ 10.5120/ijais12-450797,
author = { Shachi Sharma, Krishna Kumar Sharma, Himanshu Arora },
title = { A Natural Human-Machine Interaction via an Efficient Speech Recognition System },
journal = { International Journal of Applied Information Systems },
issue_date = { December 2012 },
volume = { 4 },
number = { 9 },
month = { December },
year = { 2012 },
issn = { 2249-0868 },
pages = { 31-37 },
numpages = {9},
url = { https://www.ijais.org/archives/volume4/number9/389-0797/ },
doi = { 10.5120/ijais12-450797 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2023-07-05T10:48:02.859117+05:30
%A Shachi Sharma
%A Krishna Kumar Sharma
%A Himanshu Arora
%T A Natural Human-Machine Interaction via an Efficient Speech Recognition System
%J International Journal of Applied Information Systems
%@ 2249-0868
%V 4
%N 9
%P 31-37
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper is motivated from non-technical users' problems in using technical interfaces of computer. In village areas, farmers face problems in using conventional ways to use computers, so in order to design a natural interaction way of human with computer, an efficient speech recognition system should be developed. For this we designed a system application. User has to speak commands and the system performs according to commands. This is all tested in the mobile environment and with varying users. And from the results, conclusion has been derived that the hybrid feature set outperformed in the noisy environment as compared to individual feature set with their dynamic features. And the result was approximately 5% higher. When DHMM is implemented in the system, results increased.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Speech Recognition system DHMM hybrid feature set