K.Prajna

Work place: Dept. of Electronics and Communication Engineering, Andhra University, India

E-mail: prajnakunche@yahoo.com

Website:

Research Interests: Computer systems and computational processes, Computer Architecture and Organization, Image and Sound Processing, Data Structures and Algorithms

Biography

K.Prajna received the B.Tech degree in ECE from Pragati Engineering College and M.Tech degree in Radar and Microwave Engineering from Andhra University in 2009. She is currently pursing Ph.D in the Department of ECE Andhra University, Visakhapatnam, India. Her area of research interests includes signal processing, speech processing and intelligent systems.

Author Articles
A New Dual Channel Speech Enhancement Approach Based on Accelerated Particle Swarm Optimization (APSO)

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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