Open AccessCombined speech compression and encryption using chaotic compressive sensing with large key size
Author(s) -
AlAzawi Maher K. Mahmood,
Gaze Ali M.
Publication year - 2018
Publication title -
iet signal processing
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.384
H-Index - 42
eISSN - 1751-9683
pISSN - 1751-9675
DOI - 10.1049/iet-spr.2016.0708
Subject(s) - pesq , computer science , encryption , speech recognition , compression ratio , speech coding , signal to noise ratio (imaging) , key (lock) , algorithm , compressed sensing , speech enhancement , noise reduction , artificial intelligence , telecommunications , physics , computer network , computer security , thermodynamics , internal combustion engine
This study introduces a new method for speech signal encryption and compression in a single step. The combined compression/encryption procedures are accomplished using compressive sensing (CS). The contourlet transform is used to increase the sparsity of the signal required by CS. Due to its randomness properties and very high sensitivity to initial conditions, the chaotic system is used to generate the sensing matrix of CS. This largely increases the key size of encryption to 10 135when logistic map is used. A spectral segmental signal‐to‐noise ratio of −36.813 dB is obtained as a measure of encryption strength. The quality of reconstructed speech is given by means of signal‐to‐noise ratio (SNR), and perceptual evaluation speech quality (PESQ). For 60% compression ratio the proposed method gives 48.203 dB SNR and 4.437 PESQ for voiced speech segments. However, for continuous speech (voiced and unvoiced), it gives 41.097 dB SNR and 4.321 PESQ.