Speech Recognition Using Articulatory and Excitation Source Features
Published on 11. January 2017
XI, 92 pages
978-3-319-49220-9 (ISBN)
Description
This book discusses the contribution of articulatory and excitation source information in discriminating sound units. The authors focus on excitation source component of speech -- and the dynamics of various articulators during speech production -- for enhancement of speech recognition (SR) performance. Speech recognition is analyzed for read, extempore, and conversation modes of speech. Five groups of articulatory features (AFs) are explored for speech recognition, in addition to conventional spectral features. Each chapter provides the motivation for exploring the specific feature for SR task, discusses the methods to extract those features, and finally suggests appropriate models to capture the sound unit specific knowledge from the proposed features. The authors close by discussing various combinations of spectral, articulatory and source features, and the desired models to enhance the performance of SR systems.
More details
Series
Edition
1st ed. 2017
Language
English
Place of publication
Cham
Switzerland
Publishing group
Springer International Publishing
Target group
Professional and scholarly
Product notice
Reflowable
Illustrations
XI, 92 p. 23 illus., 4 illus. in color.
File size
2,57 MB
ISBN-13
978-3-319-49220-9 (9783319492209)
DOI
10.1007/978-3-319-49220-9
Schweitzer Classification
Other editions
Additional editions
K. Sreenivasa Rao | Manjunath K E
Speech Recognition Using Articulatory and Excitation Source Features
Book
01/2017
Springer
€53.49
Shipment within 10-15 days
Persons
K. Sreenivasa Rao is an Associate Professor at IIT Kharagpur. He has published seven books with Springer. He published 55 Journal publications, 25 book chapters and 115 conference publications.
Content
Introduction.- Literature Review.- Articulatory Features for Phone Recognition.- Excitation Source Features for Phone Recognition.- Articulatory and Excitation Source Features for Speech Recognition in Read, Extempore and Conversation Modes.- Conclusion.- Appendix A: MFCC Features.- Appendix B: Pattern Recognition Models.
