Adaptive noise cancellation in speech signals using optimization algorithms

Speech signal quality augmentation involves the challenge to scale down the noise and to perk up the transparency In this paper the performance of two optimization algorithms is compared for denoising the speech signal. The optimization techniques such as Artificial Bee Colony(ABC), Cuckoo Search (CS)algorithm, are used as adaptive algorithms for generating the parameters of adaptive filtering function required for optimum performance. Both techniques are analyzed for different noises at different levels. Performance of these algorithms is evaluated in terms of SNR. In the analysis it is found that CS algorithm gives 45% better result than ABC.