On Four Metaheuristic Applications to Speech Enhancement－Implementing Optimization Algorithms with MATLAB R2018a

On Four Metaheuristic Applications to Speech Enhancement－Implementing Optimization Algorithms with MATLAB R2018a

This study aims to firstly implement four well-known metaheuristic optimization algorithms which, among other things, are utilized on adaptive filter design, for dual-channel speech enhancement, with voice communication devices. The implementations are conducted in a simulation fashion using MATLAB code under its newly release version of R2018a. Lately, the study takes a closer look at these four optimization methods, based on learning from the literature of the research society, on their pros and cons while applying to speech enhancement. These four methods are, namely, (1) Accelerated Particle Swarm Optimization (APSO), (2) Gravitational Search Algorithm (GSA), (3) a hybrid algorithm of PSO (Particle Swarm Optimization) and GSA (called hybrid PSOGSA), and (4) Bat Algorithm (BA). This study performs the said implementations successfully and obtains useful experimental results which contributes to building a solid foundation for more advanced research in the near future. Besides, the implementations made by the study confirm the correctness of many a previous research works which claim that these four algorithms show better performance on improved speech quality and intelligibility as compared to that of the existing standard PSO (SPSO) based speech enhancement approach.