000			03221nam a22005415i 4500
001			978-3-319-17163-0
003			DE-He213
005			20200421112220.0
007			cr nn 008mamaa
008			150331s2015 gw | s |||| 0|eng d
020			_a9783319171630 _9978-3-319-17163-0
024	7		_a10.1007/978-3-319-17163-0 _2doi
050		4	_aTK5102.9
050		4	_aTA1637-1638
050		4	_aTK7882.S65
072		7	_aTTBM _2bicssc
072		7	_aUYS _2bicssc
072		7	_aTEC008000 _2bisacsh
072		7	_aCOM073000 _2bisacsh
082	0	4	_a621.382 _223
100	1		_aRao, K. Sreenivasa. _eauthor.
245	1	0	_aLanguage Identification Using Spectral and Prosodic Features _h[electronic resource] / _cby K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity.
264		1	_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2015.
300			_aXI, 98 p. 21 illus., 5 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 Electrical and Computer Engineering, _x2191-8112
505	0		_a Introduction.- Literature Review -- Language Identification using Spectral Features -- Language Identification using Prosodic Features -- Summary and Conclusions -- Appendix A: LPCC Features -- Appendix B: MFCC Features --  Appendix C: Gaussian Mixture Model (GMM).
520			_aThis book discusses the impact of spectral features extracted from frame level, glottal closure regions, and pitch-synchronous analysis on the performance of language identification systems. In addition to spectral features, the authors explore prosodic features such as intonation, rhythm, and stress features for discriminating the languages. They present how the proposed spectral and prosodic features capture the language specific information from two complementary aspects, showing how the development of language identification (LID) system using the combination of spectral and prosodic features will enhance the accuracy of identification as well as improve the robustness of the system. This book provides the methods to extract the spectral and prosodic features at various levels, and also suggests the appropriate models for developing robust LID systems according to specific spectral and prosodic features. Finally, the book discuss about various combinations of spectral and prosodic features, and the desired models to enhance the performance of LID systems.
650		0	_aEngineering.
650		0	_aComputational linguistics.
650	1	4	_aEngineering.
650	2	4	_aSignal, Image and Speech Processing.
650	2	4	_aLanguage Translation and Linguistics.
650	2	4	_aComputational Linguistics.
700	1		_aReddy, V. Ramu. _eauthor.
700	1		_aMaity, Sudhamay. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783319171623
830		0	_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-319-17163-0
912			_aZDB-2-ENG
942			_cEBK
999			_c57324 _d57324