Metaheuristic Applications to Speech Enhancement [electronic resource] / by Prajna Kunche, K.V.V.S. Reddy.
By: Kunche, Prajna [author.].
Contributor(s): Reddy, K.V.V.S [author.] | SpringerLink (Online service).
Material type: BookSeries: SpringerBriefs in Electrical and Computer Engineering: Publisher: Cham : Springer International Publishing : Imprint: Springer, 2016Description: IX, 122 p. 50 illus., 40 illus. in color. online resource.Content type: text Media type: computer Carrier type: online resourceISBN: 9783319316833.Subject(s): Engineering | Algorithms | Computational linguistics | Engineering | Signal, Image and Speech Processing | Algorithm Analysis and Problem Complexity | Computational LinguisticsAdditional physical formats: Printed edition:: No titleDDC classification: 621.382 Online resources: Click here to access onlineIntroduction -- Adaptive Noise Cancellation to Speech Enhancement -- Heuristic and Metaheuristic Optimization -- Application of Metaheuristics to Speech Enhancement -- Speech Enhancement Based on Accelerated Particle Swarm Optimization -- Speech Enhancement Approach Based on Gravitational Search Algorithm (GSA) -- Speech Enhancement Based on Hybrid PSOGSA -- Speech Enhancement Based on Bat Algorithm -- Conclusion and Future Scope.
This book serves as a basic reference for those interested in the application of metaheuristics to speech enhancement. The major goal of the book is to explain the basic concepts of optimization methods and their use in heuristic optimization in speech enhancement to scientists, practicing engineers, and academic researchers in speech processing. The authors discuss why it has been a challenging problem for researchers to develop new enhancement algorithms that aid in the quality and intelligibility of degraded speech. They present powerful optimization methods to speech enhancement that can help to solve the noise reduction problems. Readers will be able to understand the fundamentals of speech processing as well as the optimization techniques, how the speech enhancement algorithms are implemented by utilizing optimization methods, and will be given the tools to develop new algorithms. The authors also provide a comprehensive literature survey regarding the topic.
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