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A Novel Compressed Sensing Approach to Speech Signal Compression

  • Tan N. Nguyen
  • Phuong T. Tran
  • Miroslav Voznak
Conference paper
Part of the Lecture Notes in Electrical Engineering book series (LNEE, volume 371)

Abstract

Compressed sensing (CS) is a technique to sample compressible signals below the Nyquist rate, whilst still allowing near optimal reconstruction of the signal. In this paper, we apply the iterative hard thresholding (IHT) algorithm for compressed sensing on the speech signal. The interested speech signal is transformed to the frequency domain using Discrete Fourier Transform (DCT) and then compressed sensing is applied to that signal. The compressed signal can be reconstructed using the recently introduced Iterative Hard Thresholding (IHT) algorithm and also by the tradditional \( \ell_{1} \) minimization (basic pursuit) for comparison. It is shown that the compressed sensing can provide better root mean square error (RMSE) than the tradition DCT compression method, given the same compression ratio.

Keywords

Compressed sensing Iterative hard thresholding Speech signal compression DCT \( \ell_{1} \) minimization 

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Tan N. Nguyen
    • 1
  • Phuong T. Tran
    • 1
  • Miroslav Voznak
    • 2
  1. 1.Faculty of Electrical and Electronics EngineeringTon Duc Thang UniversityHo Chi Minh CityVietnam
  2. 2.VSB-Technical University of OstravaOstrava-PorubaCzech Republic

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