Directed Searching Optimization-Based Speech Enhancement Technique
Abstract
In general, the background noise degrades the speech quality. Thus, the intelligibility of the speech can be enhanced by mitigating the effects of background noise and echo suppression. So, speech enhancement can also be viewed as one of the optimization problems. In this work, directed search optimization (DSO) method is used to enhance the speech quality which is originally degraded. The performance of DSO-based speech enhancement method is compared with particle swarm optimization (PSO) and least mean square (LMS)-based methods in terms of output average segmental SNR and speech quality. From the experimental results, it was observed that the output spectrogram, output ASSNR and speech quality using DSO algorithm are far better as compared to PSO and LMS-based methods. Moreover, DSO-based method is computationally less complex as compared to the PSO-based method.
Communicated by Ulisses Braga-Neto