Time Domain Speech Scrambler based on Particle Swarm Optimization

Hasan, Zahraa A. and Hadi, Suha M. and Mahmoud, Waleed A. (2023) Time Domain Speech Scrambler based on Particle Swarm Optimization. POLLACK PERIODICA : AN INTERNATIONAL JOURNAL FOR ENGINEERING AND INFORMATION SCIENCES, 18 (1). pp. 161-166. ISSN 1788-1994 (print); 1788-3911 (online)

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Abstract

Speech scrambler is used to transform clear speech into an unintelligible signal to prevent eavesdropping. The speech scrambling algorithm involves the permutation of speech segments depending on a specific permutation matrix which may be fixed or dynamic during encryption. A fixed permutation matrix is easy to break and has given high residual intelligibility in the scrambled signal. The proposed scheme used a particle swarm optimization algorithm to generate a dynamic permutation array that can attain a high degree of security. The outcome of the scrambled speech signal does not have any residual intelligibility, and the quality of the descrambled speech is extremely satisfying, with zero mean squared error.

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