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Through practical cases, the author explores, dissect and examine how soft computing may complement conventional techniques in speech enhancement and speech recognition in order to provide robust systems. Includes coverage of synergy between speech technology and bio-inspired soft computing methods. The material is especially useful to graduate students and experienced researchers who are interested in expanding their horizon and in investigating new research directions through a review of the theoretical and practical settings of soft computing methods in very recent speech applications.
List of contents
Part I. Soft Computing and Speech Enhancement.- 1: Speech Enhancement: Problem Formulation, Theories and Techniques.- 2: Connectionist Approaches in Speech Enhancement.- 3: Subspace-decomposition Methods.- 4: Evolutionary Algorithms and Speech Enhancement.- 5: Hybrid Approaches of Enhancement and Applications in Noisy Telecommunication Channels.- PART II: Soft Computing and Automatic Speech Recognition (ASR).- 1: Issues and Challenges of Automatic Speech Recognition. - 2: Artificial Neural Networks and Speech Recognition.- 3: Evolutionary Algorithms and Speech Recognition.- 4: Model Adaptation Using Hybrid Approaches.- 5: Applications of Robust ASR Using Soft Computing in Mobile Communications.
Summary
Speech Processing and Soft Computing includes coverage of synergy between speech technology and bio-inspired soft computing methods. Through practical cases, the author explores, dissects and examines how soft computing may complement conventional techniques in speech enhancement and speech recognition in order to provide robust systems. The material is especially useful to graduate students and experienced researchers who are interested in expanding their horizons and investigating new research directions through review of the theoretical and practical settings of soft computing methods in very recent speech applications.
