Titlebook: Metaheuristic Applications to Speech Enhancement; Prajna Kunche,K.V.V.S. Reddy Book 2016 The Author(s) 2016 Heuristic Optimization.Metaheu

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gusher

Heuristic and Meta-Heuristic Optimization,ous over the deterministic approaches are described in Sect.?.. Heuristic and meta-heuristic optimization techniques are defined in Sect.?., and it also presents various existing heuristic and meta-heuristic optimization techniques. The fundamentals of the swarm intelligence are given in Sect.?.. Th

Arthropathy

Application of Meta-Heuristics to Speech Enhancement, are described in Sect. .. The selection of the objective function for adaptive noise cancellation is described in Sect. .. This chapter discusses the previously proposed meta-heuristic algorithms to ANC in dual-channel speech enhancement. All the previously proposed methods are presented in Sect. .

hardheaded

Speech Enhancement Approach Based on Accelerated Particle Swarm Optimization (APSO),ed 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 convergenc

cancellous-bone

冥界三河

Speech Enhancement Based on Hybrid PSOGSA,lem. PSO has good exploration and lacks exploitation capability, whereas GSA has good exploitation. In this chapter, in order to get better solutions for the problem of adaptive noise cancellation, a new approach to dual-channel speech enhancement is proposed based on a recently introduced meta-heur

追逐

Speech Enhancement Based on Bat Algorithm (BA),A is developed by Yang (.). As a novel feature BA is based on the echolocation behaviour of microbats. BA uses the frequency tuning technique to increase the diversity of the solutions in the population, while at the same time it uses the automatic zooming and tries to balance the exploration and ex

凹室

Conclusions and Future Scope,SA, Hybrid PSOGSA and BA are applied to speech enhancement to enhance the input noisy speech. The performance of the proposed algorithms are compared with the performance of the existing standard PSO based speech enhancement approach. From the results it is observed that each of the proposed algorit

擴(kuò)張

xakt abgegrenzt. Dies erscheint sehr wichtig, da sowohl der Begriff der Qualit?t als auch der Begriff des E—Learnings nicht einheitlich definiert sind und in unterschiedlichen disziplinaren Kontexten unterschiedliche Bedeutungen beziehungsweise Konnotationen aufweisen. Auch der Begriff der Weiterbil