Research Article
A Fast Algorithm for HMM Training using Game Theory for Phoneme Recognition
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 118 - Issue 11 |
| Published: May 2015 |
| Authors: J. Ujwala Rekha, K. Shahu Chatrapati, A Vinaya Babu |
10.5120/20789-3432
|
J. Ujwala Rekha, K. Shahu Chatrapati, A Vinaya Babu . A Fast Algorithm for HMM Training using Game Theory for Phoneme Recognition. International Journal of Computer Applications. 118, 11 (May 2015), 21-25. DOI=10.5120/20789-3432
@article{ 10.5120/20789-3432,
author = { J. Ujwala Rekha,K. Shahu Chatrapati,A Vinaya Babu },
title = { A Fast Algorithm for HMM Training using Game Theory for Phoneme Recognition },
journal = { International Journal of Computer Applications },
year = { 2015 },
volume = { 118 },
number = { 11 },
pages = { 21-25 },
doi = { 10.5120/20789-3432 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2015
%A J. Ujwala Rekha
%A K. Shahu Chatrapati
%A A Vinaya Babu
%T A Fast Algorithm for HMM Training using Game Theory for Phoneme Recognition%T
%J International Journal of Computer Applications
%V 118
%N 11
%P 21-25
%R 10.5120/20789-3432
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Hidden Markov Models are widely used for modeling and predicting label sequences in ASR. In this paper, a game-theoretic approach for Hidden Markov Model training that is superior in terms of time-complexity over Baum-Welch algorithm is introduced. Furthermore, accuracy of recognition using proposed algorithm is comparable with that of Baum-Welch algorithm.
References
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