Abstract
This chapter introduces a recently developed new variant of PSO, called (Yang in Nature-inspired metaheuristic algorithms. Luniver Press, 2010) accelerated particle swarm optimization (APSO), to speech enhancement application. As discussed in the earlier chapter one, the limitation of the conventional PSO is the slow convergence speed of the algorithm with refined search space. Hence, as an alternative for conventional PSO, to enhance the convergence speed of enhancement algorithm, APSO is adapted to speech enhancement in the present study. Accelerated particle swarm optimization technique is developed by Yang (Nature-inspired metaheuristic algorithms. Luniver Press, 2010). APSO is simple to implement, and it has fast convergence compared to the standard PSO (SPSO). The present chapter intends to analyse the performance of APSO and to compare it with existing standard PSO algorithm in the context of dual-channel speech enhancement. The proposed algorithm is evaluated using one intelligibility measure and three speech quality measures.
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Kunche, P., Reddy, K.V.V.S. (2016). Speech Enhancement Approach Based on Accelerated Particle Swarm Optimization (APSO). In: Metaheuristic Applications to Speech Enhancement. SpringerBriefs in Electrical and Computer Engineering(). Springer, Cham. https://doi.org/10.1007/978-3-319-31683-3_5
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DOI: https://doi.org/10.1007/978-3-319-31683-3_5
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