000			04410nam a22004455i 4500
999			_c387593 _d387593
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003			ES-MaUEC
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007			cr nn 008mamaa
008			220601s2011 sz | s |||| 0|eng d
020			_a9783031025600
024	7		_a10.1007/978-3-031-02560-0 _2doi
040			_aES-MaUEC _bspa _cES-MaUEC _dES-MaUEC
050		4	_aTK7882.S65 _b2011 EB
100	1		_aBenesty, Jacob _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9673239
245	1	0	_aSpeech Enhancement in the Karhunen-Loeve Expansion Domain _cby Jacob Benesty, Jingdong Chen, Yiteng Huang
250			_a1st edition 2011
264		1	_aCham _bSpringer International Publishing _c2011
300			_a1 recurso en línea (IX, 102 páginas)
336			_atexto _btxt _2rdacontent
337			_aelectrónico _bc _2rdamedia
338			_arecurso electrónico _bcr _2rdacarrier
347			_aarchivo de texto _bPDF
490	0		_aSynthesis Lectures on Speech and Audio Processing _x1932-1678
505	0		_aIntroduction -- Problem Formulation -- Optimal Filters in the Time Domain -- Linear Models for Signal Enhancement in the KLE Domain -- Optimal Filters in the KLE Domain with Model 1 -- Optimal Filters in the KLE Domain with Model 2 -- Optimal Filters in the KLE Domain with Model 3 -- Optimal Filters in the KLE Domain with Model 4 -- Experimental Study.
520			_aThis book is devoted to the study of the problem of speech enhancement whose objective is the recovery of a signal of interest (i.e., speech) from noisy observations. Typically, the recovery process is accomplished by passing the noisy observations through a linear filter (or a linear transformation). Since both the desired speech and undesired noise are filtered at the same time, the most critical issue of speech enhancement resides in how to design a proper optimal filter that can fully take advantage of the difference between the speech and noise statistics to mitigate the noise effect as much as possible while maintaining the speech perception identical to its original form. The optimal filters can be designed either in the time domain or in a transform space. As the title indicates, this book will focus on developing and analyzing optimal filters in the Karhunen-Loève expansion (KLE) domain. We begin by describing the basic problem of speech enhancement and the fundamental principles to solve it in the time domain. We then explain how the problem can be equivalently formulated in the KLE domain. Next, we divide the general problem in the KLE domain into four groups, depending on whether interframe and interband information is accounted for, leading to four linear models for speech enhancement in the KLE domain. For each model, we introduce signal processing measures to quantify the performance of speech enhancement, discuss the formation of different cost functions, and address the optimization of these cost functions for the derivation of different optimal filters. Both theoretical analysis and experiments will be provided to study the performance of these filters and the links between the KLE-domain and time-domain optimal filters will be examined. Table of Contents: Introduction / Problem Formulation / Optimal Filters in the Time Domain / Linear Models for Signal Enhancement in the KLE Domain / Optimal Filters in the KLE Domain with Model 1 / Optimal Filters in the KLE Domain with Model 2 / Optimal Filters in the KLE Domain with Model 3 / Optimal Filters in the KLE Domain with Model 4 / Experimental Study.
988			_aSynthesis Collection of Technology_2011
650		7	_2embne _9150609 _aProceso digital de señales
650		7	_2embne _9666075 _aLingüística computacional
650		7	_2embne _9687635 _aFiltros eléctricos digitales
700	1		_aChen, Jingdong _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9100906
700	1		_aHuang, Yiteng _eautor _4aut _4http://id.loc.gov/vocabulary/relators/aut _9686496 _d1972-
776	0	8	_iPrinted edition: _z9783031014321
776	0	8	_iPrinted edition: _z9783031036880
856	4	0	_uhttps://go.openathens.net/redirector/universidadeuropea.es?url=https://doi.org/10.1007/978-3-031-02560-0 _zAcceso a este recurso digital (usuarios Universidad Europea de Madrid)
942			_2lcc _cLE
998			_b03/2023 _dz _esc _zSI