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 synergybetween 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. Focuses on the missing link between speech technology and soft computing. Contains coverage of the innovative approaches in speech technology. Gives new insights in speech recognition/enhancement obtained by investigating solutions beyond the statistical approach. INDICE: 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.
- ISBN: 978-1-4419-9684-8
- Editorial: Springer New York
- Encuadernacion: Rústica
- Páginas: 120
- Fecha Publicación: 11/11/2011
- Nº Volúmenes: 1
- Idioma: Inglés