A New Dual Channel Speech Enhancement Approach Based on Accelerated Particle Swarm Optimization (APSO)
Author(s) -
K. Prajna,
G. Sasi Bhushan Rao,
K. V. V. S. Reddy,
R. Maheswari
Publication year - 2014
Publication title -
international journal of intelligent systems and applications
Language(s) - English
Resource type - Journals
eISSN - 2074-9058
pISSN - 2074-904X
DOI - 10.5815/ijisa.2014.04.01
Subject(s) - particle swarm optimization , pesq , computer science , speech enhancement , intelligibility (philosophy) , algorithm , speech recognition , mathematical optimization , artificial intelligence , noise reduction , mathematics , philosophy , epistemology
This research paper proposes a recently developed new variant of Particle Swarm Optimization (PSO) called Accelerated Particle Swarm Optimization (APSO) in speech enhancement application. Accelerated Particle Swarm Optimization technique is developed by Xin she Yang in 2010. APSO is simpler to implement and it has faster convergence when compared to the standard PSO (SPSO) algorithm. Hence as an alternative to SPSO based speech enhancement algorithm, APSO is introduced to speech enhancement in the present paper. The present study aims to analyze the performance of APSO and to compare it with existing standard PSO algorithm, in the context of dual channel speech enhancement. Objective evaluation of the proposed method is carried out by using three objective measures of speech quality SNR, Improved SNR, PESQ and one objective measure of speech intelligibility FAI. The performance of the algorithm is studied under babble and factory noise environments. Simulation result proves that APSO based speech enhancement algorithm is superior to the standard PSO based algorithm with an improved speech quality and intelligibility measures.
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