Work place: Dept. of Electronics and Communication Engineering, Vignan Institue of Information Technology, India
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Research Interests: Computer systems and computational processes, Image Compression, Image Manipulation, Image Processing
Biography
R.Uma Maheswari received the B.Tech degree in ECE from MVGR college of Engineering and the M.Tech degree in VLSI System Design from Avanthi Institute of Engineering & Technology, in 2012. Presently Working as Assistant Professor in Vignan’s Institute of Information Technology, Visakhapatnam. Previously, she worked as Assistant Professor in Avanthi College of Engineering, which is affiliated to JNTU. She worked as IT- Associate in IEG (Institute for electronic Governance), Hyderabad for about one year. Her research interest includes Signal Processing, Communication systems & Image processing.
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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