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Advances in Voice Enabled Human Machine Communication

by Shweta Sinha, S. S Agrawal, Aruna Jain
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 60 - Number 17
Year of Publication: 2012
Authors: Shweta Sinha, S. S Agrawal, Aruna Jain
10.5120/9785-4356

Shweta Sinha, S. S Agrawal, Aruna Jain . Advances in Voice Enabled Human Machine Communication. International Journal of Computer Applications. 60, 17 ( December 2012), 27-33. DOI=10.5120/9785-4356

@article{ 10.5120/9785-4356,
author = { Shweta Sinha, S. S Agrawal, Aruna Jain },
title = { Advances in Voice Enabled Human Machine Communication },
journal = { International Journal of Computer Applications },
issue_date = { December 2012 },
volume = { 60 },
number = { 17 },
month = { December },
year = { 2012 },
issn = { 0975-8887 },
pages = { 27-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume60/number17/9785-4356/ },
doi = { 10.5120/9785-4356 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T21:07:13.505430+05:30
%A Shweta Sinha
%A S. S Agrawal
%A Aruna Jain
%T Advances in Voice Enabled Human Machine Communication
%J International Journal of Computer Applications
%@ 0975-8887
%V 60
%N 17
%P 27-33
%D 2012
%I Foundation of Computer Science (FCS), NY, USA
Abstract

The inherent advantage of speech communication due to its variability, convenience and speed along with our increasing requirements to communicate with machines has driven the attention of researchers towards mechanical recognition of speech. Technological advancements and improvements in the fundamental approaches have shown a successful transition from small vocabulary isolated word recognition to large vocabulary continuous speech recognition. Even after years of research and development the accuracy of automatic speech recognition remains one of the major challenges. Design of speech recognition system requires careful selection of feature extraction technique and modeling approach to cover the challenges faced due to variability of speech-speaker characteristic, storage space and processing speed requirements. In this paper an effort has been made to highlight the progress made so far for mechanizing the recognition of speech along with the major challenges in this field. Authors have also presented a brief description of voice enabled service for common people. The objective of this paper is to summarize some of the well known methods used at various stages of speech recognition system along with their benefits and limitations.

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Index Terms

Computer Science
Information Sciences

Keywords

Dynamic Time Warping Feature Extraction Hidden Markov Model Neural Network Speech Recognition

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