access icon free Combined speech compression and encryption using chaotic compressive sensing with large key size

© The Institution of Engineering and Technology
Received 13/01/2017, Accepted 21/09/2017, Revised 17/08/2017, Published 21/09/2017

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 when 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.

Inspec keywords: compressed sensing; cryptography; speech coding; transforms; signal reconstruction; data compression; matrix algebra

Other keywords: contourlet transform; signal sparsity; speech reconstruction; PESQ; spectral segmental signal-to-noise ratio; perceptual evaluation speech quality; speech compression; noise figure -36.813 dB; speech signal encryption; noise figure 48.203 dB; CS; chaotic compressive sensing matrix; noise figure 41.097 dB; SNR

Subjects: Cryptography; Integral transforms; Integral transforms; Speech processing techniques; Algebra; Speech and audio coding; Algebra; Signal processing and detection

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