Research Article
Noisy Speech Recognition by Mel-LPC based AR-HMM with Power and Time Derivative Parameters
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
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| Volume 180 - Issue 42 |
| Published: May 2018 |
| Authors: M. Babul Islam |
10.5120/ijca2018917149
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M. Babul Islam . Noisy Speech Recognition by Mel-LPC based AR-HMM with Power and Time Derivative Parameters. International Journal of Computer Applications. 180, 42 (May 2018), 1-5. DOI=10.5120/ijca2018917149
@article{ 10.5120/ijca2018917149,
author = { M. Babul Islam },
title = { Noisy Speech Recognition by Mel-LPC based AR-HMM with Power and Time Derivative Parameters },
journal = { International Journal of Computer Applications },
year = { 2018 },
volume = { 180 },
number = { 42 },
pages = { 1-5 },
doi = { 10.5120/ijca2018917149 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2018
%A M. Babul Islam
%T Noisy Speech Recognition by Mel-LPC based AR-HMM with Power and Time Derivative Parameters%T
%J International Journal of Computer Applications
%V 180
%N 42
%P 1-5
%R 10.5120/ijca2018917149
%I Foundation of Computer Science (FCS), NY, USA
Abstract
In this paper, AR-HMM on mel-scale with power and Mel-LPC based time derivative parameters has been presented for noisy speech recognition. The mel-scaled AR coefficients and melprediction coefficients for Mel-LPC have been calculated on the linear frequency scale from the speech signal without applying bilinear transformation. This has been done by using a first-order allpass filter instead of unit delay. In addition, Mel-Wiener filter has been applied to the system to improve the recognition accuracy in presence of additive noise. The proposed system is evaluated on Aurora 2 database, and the overall recognition accuracy has been found to be 80.02% on the average.
References
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