Research Article
A Comparative Study of Phoneme Recognition using GMM-HMM and ANN based Acoustic Modeling
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 98 - Issue 6 |
| Published: July 2014 |
| Authors: Farheen Fauziya, Geeta Nijhawan |
10.5120/17186-7366
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Farheen Fauziya, Geeta Nijhawan . A Comparative Study of Phoneme Recognition using GMM-HMM and ANN based Acoustic Modeling. International Journal of Computer Applications. 98, 6 (July 2014), 12-16. DOI=10.5120/17186-7366
@article{ 10.5120/17186-7366,
author = { Farheen Fauziya,Geeta Nijhawan },
title = { A Comparative Study of Phoneme Recognition using GMM-HMM and ANN based Acoustic Modeling },
journal = { International Journal of Computer Applications },
year = { 2014 },
volume = { 98 },
number = { 6 },
pages = { 12-16 },
doi = { 10.5120/17186-7366 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2014
%A Farheen Fauziya
%A Geeta Nijhawan
%T A Comparative Study of Phoneme Recognition using GMM-HMM and ANN based Acoustic Modeling%T
%J International Journal of Computer Applications
%V 98
%N 6
%P 12-16
%R 10.5120/17186-7366
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Phoneme is the smallest analogous unit of sound employed to form meaningful contrast between utterances. Hidden Markov Model (HMM), Gaussian Mixture model (GMM) and Artificial Neural Network (ANN) have been used in this paper to measure the accuracy and performance of recognition system using toolkits HTK, Sphinx3 and Quicknet, which are freely available for academic works. In this paper the performance of an ASR System based on Accuracy has been compared with TIMIT database.
References
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