A comparative study between Discrete Wavelet Transform and Linear Predictive Coding

Author

Ambika, D. ; Radha, V.

Author_Institution

Dept. of Comput. Sci., Avinashilingam Inst. for Home Sci. & Higher Educ. for Women, Coimbatore, India

fYear

2012

fDate

Oct. 30 2012-Nov. 2 2012

Firstpage

965

Lastpage

969

Abstract

In this paper the analysis of the compression process was performed by comparing the compressed signal against the original signal. To do this the most powerful speech analysis and compression techniques such as Linear Predictive Coding (LPC) and Discrete Wavelet Transform (DWT) was implemented using MATLAB. Here nine samples of spoken words are collected from different speakers and are used for implementation. The results obtained from LPC were compared with other compression technique called Discrete Wavelet Transform. Finally the results were evaluated in terms of compressed ratio (CR), Peak signal-to-noise ratio (PSNR) and Normalized root-mean square error (NRMSE). The result shows that DWT performance was better for these samples than the LPC method.

Keywords

discrete wavelet transforms; linear predictive coding; speech processing; DWT performance; MATLAB; PSNR; compressed ratio; compressed signal; discrete wavelet transform; linear predictive coding; normalized root mean square error; peak signal to noise ratio; speakers; speech analysis; spoken words; Discrete wavelet transforms; Linear predictive coding; PSNR; Speech; Speech coding; CR; DWT; LPC; NRMSE; PSNR; Speech compression;

fLanguage

English

Publisher

ieee

Conference_Titel

Information and Communication Technologies (WICT), 2012 World Congress on

Conference_Location

Trivandrum

Print_ISBN

978-1-4673-4806-5

Type

conf

DOI

10.1109/WICT.2012.6409214

Filename

6409214