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001			102941
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005			20230102113107.0
007			cr nn 008mamaa
008			171129s2018 gw | s |||| 0|eng d
020			_a9783319690025
024	7		_a10.1007/978-3-319-69002-5 _2doi
040			_aES-MaUEC _bspa
050		4	_aTK7882.S65 _bF376 2018 EB
100	1		_aFarouk, Mohamed Hesham _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _1http://viaf.org/viaf/316028437/
245	1	0	_aApplication of Wavelets in Speech Processing _cby Mohamed Hesham Farouk.
250			_a2nd ed. 2018.
264		1	_aCham _bSpringer International Publishing _c2018
300			_a1 recurso en línea (XIV, 86 páginas 25 ilustraciones, 12 ilustraciones a color)
347			_atext file _bPDF
490	0		_aSpringerBriefs in Speech Technology, Studies in Speech Signal Processing, Natural Language Understanding, and Machine Learning _x2191-737X
505	0		_aChapter 1. Introduction -- Chapter 2. Speech Production and Perception -- Chapter 3.Wavelets, Wavelet Filters and Wavelet Transforms -- Chapter 4. Spectral analysis of speech signal and Pitch estimation -- Chapter 5.Speech detection and separation -- Chapter 6.Speech Enhancement and Noise Suppression -- Chapter 7.Speech Recognition -- Chapter 8.Speaker Identification -- chapter 9.Emotion Recognition from Speech -- Chapter 10.Speech Coding, Synthesis and Compression -- Chapter 11.Speech Quality Assessment -- Chapter 12. Scalogram and Nonlinear Analysis Of Speech -- Chapter 13. Steganography, Forensics and Security of Speech signal -- Chapter 14. Clinical Diagnosis and Assessment of Speech Pathology.
520	3		_aThis new edition provides an updated and enhanced survey on employing wavelets analysis in an array of applications of speech processing. The author presents updated developments in topics such as; speech enhancement, noise suppression, spectral analysis of speech signal, speech quality assessment, speech recognition, forensics by Speech, and emotion recognition from speech. The new edition also features  a new chapter on scalogram analysis of speech. Moreover, in this edition, each chapter is restructured as such; that it becomes self contained, and can be read separately. Each chapter surveys the literature in a topic such that the use of wavelets in the work is explained and experimental results of proposed method are then discussed. Illustrative figures are also added to explain the methodology of each work.
650		7	_aReconocimiento automático del lenguaje _2embne _9147323
650		7	_aAnálisis armónico _9667393 _2embne
776	0	8	_iEdición impresa: _z9783319690018
776	0	8	_iEdición impresa: _z9783319690032
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-319-69002-5 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
490	0		_aEngineering (Springer-11647)
988			_aEBSPRINGER_2018
998			_b02/2019 _dz _ek _feng _ggw _h0
999			_c102941 _d102941 _x1