Dual channel speech enhancement using particle swarm optimization

Adaptive processing for canceling noise is a powerful technology signal that can completely remove background noise. In general, various adaptive filter algorithms are used, many of which lack the stability to handle convergence rate, number coefficient variations, and error accuracy within tolerances. Unlike traditional methods, accomplish these desirable characteristics as well efficiently cancel noise, in this paper, cancelation formulated problem optimization, where particle swarm optimization (PSO) employed. The PSO structured minimize by using very short segment corrupted speech. contrast recent conventional cancellation simulation results indicate proposed algorithm has better capability cancelation. show great improvement ratio (SNR) 96.07 dB 124.54 finite impulse response (FIR) infinite (IIR) filters respectively.