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Swarm Intelligence based computing techniques in speech enhancement

Speech enhancement has become an important topic in Digital Signal Processing Systems, as the main problem in speech enhancement is the presence of background noise which leads to the degradation of the quality of the speech signals. Removal of background noise and echo suppression has become necessary so that the intelligibility of the speech signal is improved. This may be achieved by adaptive filter. In this work, a comparative analysis between the Gradient based algorithms that is the LMS (least mean square) and RLS (recursive least square) and the swarm intelligence based global optimization algorithm such as PSO (particle swarm optimization) and ABC (Artificial Bee Colony) is discussed. The experimental results shows that swarm Intelligence based optimization algorithm techniques appears to give a better SNR(Signal to Noise Ratio) improvement than the conventional gradient based algorithm.