Combined speech compression and encryption using chaotic compressive sensing with large key size
| Autor: | Ali M. Gaze, Maher K. Mahmood Al-Azawi |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
business.industry
Computer science Signal reconstruction Speech recognition Speech coding 020206 networking & telecommunications 020207 software engineering 02 engineering and technology Encryption Contourlet Compressed sensing Signal Processing Compression ratio 0202 electrical engineering electronic engineering information engineering Electrical and Electronic Engineering business PESQ Data compression |
| Zdroj: | IET Signal Processing. 12:214-218 |
| ISSN: | 1751-9683 1751-9675 |
| DOI: | 10.1049/iet-spr.2016.0708 |
| Popis: | 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 10 135 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. |
| Databáze: | OpenAIRE |
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