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Journal of applied research and technology
On-line version ISSN 2448-6736Print version ISSN 1665-6423
Abstract
FISLI, Sofiane and DJENDI, Mohamed. New modified Bat algorithm for blind speech enhancement in time domain. J. appl. res. technol [online]. 2023, vol.21, n.6, pp.982-990. Epub Aug 13, 2024. ISSN 2448-6736. https://doi.org/10.22201/icat.24486736e.2023.21.6.1931.
We address the speech enhancement problem for dual convolutif mixed channel by viewing it in a blind separation source setting. One widely used technique to separate mixed signals is to apply adaptive filtering, the challenge is to identify an unknown finite impulse response. Traditionally we apply a gradient-based algorithm to adapt filter coefficients. However, such algorithms often suffer from premature convergence when using large filters and non-stationary inputs leading to the so-called local minimum problem, which affects the quality of enhanced signals significatively. One alternative to overcome this problem is to apply a population-based metaheuristic algorithms in which filter coefficients are adapted iteratively by minimizing a cost function. But even with this metaheuristic-based solution, local minimum problem at large filters still exist. To avoid local minima and improve the chance to reach the global solution. We propose in this paper, a novel algorithm called a modified Bat algorithm to render the search process efficiently by enhancing its capability of exploration and exploitation. Several experiments under different noise types are conducted using our proposed modified Bat algorithm in comparison with some of the popular state-of-the-art algorithms. The enhanced signals obtained by each algorithm at the separation process outputs show good behavior and superiority of our proposed algorithm. In terms of system misalignment, as well as a segmental signal-to-noise ratio.
Keywords : Speech enhancement; blind source separation; population-based metaheuristic algorithms; system misalignment; segmental signal-to-noise ratio.
