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020 _a9783319492209
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024 7 _a10.1007/978-3-319-49220-9
_2doi
050 4 _aTK5102.9
072 7 _aTJF
_2bicssc
072 7 _aUYS
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082 0 4 _a621.382
_223
100 1 _aRao, K. Sreenivasa.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961661
245 1 0 _aSpeech Recognition Using Articulatory and Excitation Source Features
_h[electronic resource] /
_cby K. Sreenivasa Rao, Manjunath K E.
250 _a1st ed. 2017.
264 1 _aCham :
_bSpringer International Publishing :
_bImprint: Springer,
_c2017.
300 _aXI, 92 p. 23 illus., 4 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
_x2191-7388
505 0 _aIntroduction -- 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.
520 _aThis 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.
650 0 _aSignal processing.
_94052
650 0 _aNatural language processing (Computer science).
_94741
650 0 _aComputational linguistics.
_96146
650 1 4 _aSignal, Speech and Image Processing .
_931566
650 2 4 _aNatural Language Processing (NLP).
_931587
650 2 4 _aComputational Linguistics.
_96146
700 1 _aK E, Manjunath.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
_961662
710 2 _aSpringerLink (Online service)
_961663
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9783319492193
776 0 8 _iPrinted edition:
_z9783319492216
830 0 _aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning,
_x2191-7388
_961664
856 4 0 _uhttps://doi.org/10.1007/978-3-319-49220-9
912 _aZDB-2-ENG
912 _aZDB-2-SXE
942 _cEBK
999 _c80802
_d80802