Work place: Dept. of Electronics and Communication Engineering, Andhra University, India
E-mail: konalavs@yahoo.com
Website:
Research Interests: Engineering
Biography
Dr. K.V.V.S. Reddy is a former Professor of Electronics and Communication Engineering in Andhra University College of Engineering. He has published more than 70 journal and conference papers. He has 33 years of experience in teaching and research besides possessing 3 years of industrial experience. He is a Fellow of Institute of Electronics and Telecommunication Engineers (FIETE) and Life Member Society for EMI/EMC Engineers, India. He has produced 10 Ph.Ds and few more research scholars are actively working under his guidance towards their Ph.D. He has guided more than 70 M.E & M.Tech projects. His areas of research interest are Communication systems, Signal Processing and Satellite Communications.
By K.Prajna G.Sasi Bhushan Rao K.V.V.S.Reddy R.Uma Maheswari
DOI: https://doi.org/10.5815/ijisa.2014.04.01, Pub. Date: 8 Mar. 2014
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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