Speech Recognition Using Articulatory and Excitation Source Features (Paperback, 1st ed. 2017)

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.

General

Imprint:	Springer International Publishing AG
Country of origin:	Switzerland
Series:	SpringerBriefs in Speech Technology
Release date:	2017
First published:	2017
Authors:	K. Sreenivasa Rao • Manjunath K E
Dimensions:	235 x 155 x 6mm (L x W x T)
Format:	Paperback
Pages:	92
Edition:	1st ed. 2017
ISBN-13:	978-3-319-49219-3
Categories:	Books > Language & Literature > Language & linguistics > Computational linguistics Books > Computing & IT > Applications of computing > Artificial intelligence > Natural language & machine translation Books > Professional & Technical > Electronics & communications engineering > Electronics engineering > Applied optics > General
LSN:	3-319-49219-5
Barcode:	9783319492193

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