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.

Focuses on articulatory features and various groups present within the general AFs Proposes robust signal processing methods for extracting the excitation source features from LP residual signal Discusses various mapping functions for extracting the AFs from spectral features and appropriate non-linear models for realizing the accurate mapping functions for the shape of vocal tract to movements of articulators Includes supplementary material: sn.pub/extras

Autorentext

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.

Inhalt
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.