Title :
Improved Particle Swarm Optimization for Dual-Channel Speech Enhancement
Author :
Asl, Laleh Badri ; Nezhad, Vahid Majid
Author_Institution :
Fac. of Electr. & Comput. Eng., Univ. of Tabriz, Tabriz, Iran
Abstract :
This paper, proposes an improved particle swarm optimization algorithm for speech enhancement. In the proposed algorithm, the population is divided into two subgroups. One of the subgroups searches the space globally, whereas the other one explores the problem space locally. The proposed algorithm surpasses the standard PSO, by stimulating the inactive particles and local search around the global best. Experimental results indicate that improved particle swarm optimization (IPSO) outperforms the standard particle swarm optimization (SPSO), and gradient-based NLMS algorithm in dual-channel speech enhancement applications.
Keywords :
gradient methods; particle swarm optimisation; speech enhancement; dual-channel speech enhancement; gradient-based NLMS algorithm; improved particle swarm optimization; population division; standard particle swarm optimization; Application software; Filtering; Kalman filters; Least squares approximation; Particle swarm optimization; Signal processing; Space exploration; Speech enhancement; Stochastic processes; Wiener filter; Improved Particle Swarm Optimization (IPSO); Speech Enhancement; Standard Particle Swarm Optimization (SPSO);
Conference_Titel :
Signal Acquisition and Processing, 2010. ICSAP '10. International Conference on
Conference_Location :
Bangalore
Print_ISBN :
978-1-4244-5724-3
Electronic_ISBN :
978-1-4244-5725-0
DOI :
10.1109/ICSAP.2010.30
