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Reseach Article

Comparison of Different Speech Feature Extraction Techniques with and without Wavelet Transform to Kannada Speech Recognition

by M.A.Anusuya, S.K.Katti
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 26 - Number 4
Year of Publication: 2011
Authors: M.A.Anusuya, S.K.Katti
10.5120/3092-4242

M.A.Anusuya, S.K.Katti . Comparison of Different Speech Feature Extraction Techniques with and without Wavelet Transform to Kannada Speech Recognition. International Journal of Computer Applications. 26, 4 ( July 2011), 19-23. DOI=10.5120/3092-4242

@article{ 10.5120/3092-4242,
author = { M.A.Anusuya, S.K.Katti },
title = { Comparison of Different Speech Feature Extraction Techniques with and without Wavelet Transform to Kannada Speech Recognition },
journal = { International Journal of Computer Applications },
issue_date = { July 2011 },
volume = { 26 },
number = { 4 },
month = { July },
year = { 2011 },
issn = { 0975-8887 },
pages = { 19-23 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume26/number4/3092-4242/ },
doi = { 10.5120/3092-4242 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T20:11:56.725714+05:30
%A M.A.Anusuya
%A S.K.Katti
%T Comparison of Different Speech Feature Extraction Techniques with and without Wavelet Transform to Kannada Speech Recognition
%J International Journal of Computer Applications
%@ 0975-8887
%V 26
%N 4
%P 19-23
%D 2011
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Pre-processing of speech signals is considered a crucial step in the development of a robust and efficient speech or speaker recognition system. This paper deals with different speech processing techniques and the recognition accuracy with respect to wavelet transforms. It is shown that by applying wavelet transform to the conventional methods the signal recognition accuracy will be increased by using discrete wavelet transforms and the wavelet packets for clean and noisy speech signals respectively. Results presented in the tabular form, shows the advantage of pre-processing the signals with wavelet techniques gives good results over conventional methods.

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Index Terms

Computer Science
Information Sciences

Keywords

Speech signal pre-processing Discrete Wavelets Transforms(DWT) Wavelet packet decomposition (WPD) Linear Predictive co-efficient (LPC) kannada isolated words Mel frequency cepstral co-efficient (MFCC) RelAtive Spectral Transform- Perceptual Linear Prediction approach (RASTA-PLP) Euclidean distance