Effects of Using Static Methods with Contourlet Transformation on Speech Compression

  • Esraa Abd Alsalam College of Education for Pure Science, Department of Computer Science, University of Mosul, Iraq
  • Shaymaa Ahmed Razoqi College of Education for Pure Science, Department of Computer Science, University of Mosul, Iraq
  • Eman Fathi Ahmed College of Education for Pure Science, Department of Computer Science, University of Mosul, Iraq
Keywords: Speech compression, Contourlet transformation, IQR, AAD, MAD, STD

Abstract

Compression of speech signal is an essential field in signal processing. Speech compression is very important in today’s world, due to the limited bandwidth transmission and storage capacity. This paper explores a Contourlet transformation based methodology for the compression of the speech signal. In this methodology, the speech signal is analysed using Contourlet transformation coefficients with statistic methods as threshold values, such as Interquartile Filter (IQR), Average Absolute Deviation (AAD), Median Absolute Deviation (MAD) and standard deviation (STD), followed by the application of (Run length encoding) They are exploited for recording speech in different times (5, 30, and 120 seconds). A comparative study of performance of different transforms is made in terms of (Signal to Noise Ratio,Peak Signal to Noise Ratio,Normalized Cross-Correlation, Normalized Cross-Correlation) and the compression ratio (CR). The best stable result of implementing our algorithm for compressing speech is at level1 with   AAD or MAD, adopting Matlab 2013a language.

Published
2021-08-31
How to Cite
Abd Alsalam, E., Razoqi, S. A., & Ahmed, E. F. (2021). Effects of Using Static Methods with Contourlet Transformation on Speech Compression. Iraqi Journal of Science, 62(8), 2784-2795. https://doi.org/10.24996/ijs.2021.62.8.31
Section
Computer Science