Speech recognition using articulatory and excitation source features

"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) pe...

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Bibliographic Details
Main Authors: Rao, K. Sreenivasa (Author), Manjunath K. E., (Author)
Format: eBook
Language: English
Published: Cham, Switzerland : Springer, [2017]
Series: SpringerBriefs in electrical and computer engineering. Speech technology.
Subjects:
Automatic speech recognition.
elektronické knihy
electronic books
ISBN: 9783319492209
9783319492193
Physical Description: 1 online resource (92 pages) : illustrations

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020 |z 9783319492193  |q (paper) 
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100 1 |a Rao, K. Sreenivasa  |q (Krothapalli Sreenivasa),  |e author. 
245 1 0 |a Speech recognition using articulatory and excitation source features /  |c K. Sreenivasa Rao, Manjunath K.E. 
264 1 |a Cham, Switzerland :  |b Springer,  |c [2017] 
264 4 |c ©2017 
300 |a 1 online resource (92 pages) :  |b illustrations 
336 |a text  |b txt  |2 rdacontent 
337 |a počítač  |b c  |2 rdamedia 
338 |a online zdroj  |b cr  |2 rdacarrier 
490 1 |a SpringerBriefs in electrical and computer engineering. Speech technology 
504 |a Includes bibliographical references. 
505 0 |a 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. 
506 |a Plný text je dostupný pouze z IP adres počítačů Univerzity Tomáše Bati ve Zlíně nebo vzdáleným přístupem pro zaměstnance a studenty 
520 |a "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"--Provided by publisher. 
590 |a SpringerLink  |b Springer Complete eBooks 
650 0 |a Automatic speech recognition. 
655 7 |a elektronické knihy  |7 fd186907  |2 czenas 
655 9 |a electronic books  |2 eczenas 
700 0 |a Manjunath K. E.,  |e author. 
776 0 8 |i Print version:  |a Rao, K. Sreenivasa (Krothapalli Sreenivasa).  |t Speech recognition using articulatory and excitation source features.  |d Cham, Switzerland : Springer, [2017]  |z 3319492195  |w (OCoLC)960835632 
830 0 |a SpringerBriefs in electrical and computer engineering.  |p Speech technology. 
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992 |c NTK-SpringerENG 
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993 |x NEPOSILAT  |y EIZ 

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