An Efficient Convolutional Blind Source Separation Algorithm for Speech Signals under Chaotic Masking

Abstract

As the main method of information transmission, it is particularly important to ensure the security of speech communication. Considering the more complex multipath channel transmission situation in the wireless communication of speech signals and separating or extracting the source signal from the convolutional signal are crucial steps in obtaining source information. In this paper, chaotic masking technology is used to guarantee the transmission safety of speech signals, and a fast fixed-point independent vector analysis algorithm is used to solve the problem of convolutional blind source separation. First, the chaotic masking is performed before the speech signal is sent, and the convolutional mixing process of multiple signals is simulated by impulse response filter. Then, the observed signal is transformed to the frequency domain by short-time Fourier transform, and instantaneous blind source separation is performed using a fast fixed-point independent vector analysis algorithm. The algorithm can preserve the high-order statistical correlation between frequencies to solve the permutation ambiguity problem in independent component analysis. Simulation experiments show that this algorithm can efficiently complete the blind extraction of convolutional signals, and the quality of recovered speech signals is better. It provides a solution for the secure transmission and effective separation of speech signals in multipath transmission channels.

Blind Source Separation Based on Double-Mutant Butterfly Optimization Algorithm

“…Blind source separation (BSS), sometimes referred to as blind signal processing, is capable of recovering a source signal from an observed signal in the absence of critical information, such as source and channel [ 1 , 2 , 3 ]. Due to its high adaptability and other advantages, BSS has been employed in a variety of research fields in recent years, such as image processing, medical evaluation, radar analysis, speech recognition, and machinery [ 4 , 5 , 6 , 7 , 8 ].…”