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007			cr nn 008mamaa
008			150331s2015 gw | s |||| 0|eng d
020			_a9783319171630
024	7		_a10.1007/978-3-319-17163-0 _2doi
040			_bspa _dES-MaUEC _cES-MaUEC
050		4	_aP126 _b2015 EB
100	1		_aRao, K. Sreenivasa. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _0http://id.loc.gov/authorities/names/no2004024924 _1http://viaf.org/viaf/65926948/
245	1	0	_aLanguage Identification Using Spectral and Prosodic Features _cby K. Sreenivasa Rao, V. Ramu Reddy, Sudhamay Maity.
264		1	_aCham _bSpringer International Publishing _c2015
300			_a1 recurso en línea (XI, 98 páginas 21 ilustraciones, 5 ilustraciones a color.)
336			_2rdacontent _aTexto (visual) _btxt
337			_2rdamedia _aelectrónico _bc
338			_2rdacarrier _arecurso electrónico _bcr
490	0		_aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning, _x2191-737X
490	0		_aEngineering (Springer-11647)
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	3		_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.
988			_aEBSPRINGER_2018
650		7	_2embne _aAnálisis lingüístico _9156443
700	1		_aReddy, V. Ramu. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
700	1		_aMaity, Sudhamay. _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut
776	0	8	_iEdición impresa: _z9783319171623
776	0	8	_iEdición impresa: _z9783319171647
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-17163-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b05/2019 _dz _ejf _zSI