Performance evaluation of speech scrambling methods based on statistical approach

• Autores: Sattar B. Sadkhan, Nidaa A. Abbas
• Localización: Atti della Fondazione Giorgio Ronchi, ISSN 0391-2051, Anno 66, Nº. 5, 2011, págs. 601-614
• Idioma: inglés
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• Resumen

  • The speech scrambling plays a great role in many important communication systems, such as military communications and banks communication systems. There are many traditional scrambling methods used in single dimension such as lime or frequency domain scrambling. This paper propose a comparison between speech scrambler methods using methods based on statistical metrics called Independent Component Analysis (lCA) and Principal Component Analysis (PCA). For lCA method, Approximate Diagonalization of Eigen-matrices (JADE) algorithm was implemented while for PCA, traditional PCA algorithm was implemented. The paper takes into consideration the testability of many input speech signals in English in two types of bits 8 bits and 16 bits. The objective test using Linear Predictive Coding (LPC), Signal-to-Noise Ratio (SNR) where applied to evaluate the scrambling systems under consideration.