Speech Signal Compression Using Wavelet AndLinear Predictive Coding

A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen le...

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Bibliographic Details
Main Authors: Ahlam Hanoon, Dr. Tarik Zeyad
Format: article
Language:EN
Published: Al-Khwarizmi College of Engineering – University of Baghdad 2005
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Online Access:https://doaj.org/article/b9a1fb3af6ee437fb22244476b0252a8
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Summary:A new algorithm is proposed to compress speech signals using wavelet transform and linear predictive coding. Signal compression based on the concept of selecting a small number of approximation coefficients after they are compressed by the wavelet decomposition (Haar and db4) at a suitable chosen level and ignored details coefficients, and then approximation coefficients are windowed by a rectangular window and fed to the linear predictor. Levinson Durbin algorithm is used to compute LP coefficients, reflection coefficients and predictor error. The compress files contain LP coefficients and previous sample. These files are very small in size compared to the size of the original signals. Compression ratio is calculated from the size of the compressed signal relative to the size of the uncompressed signal. The proposed algorithms where fulfilled with the use of Matlab package.