000			03816nam a22005655i 4500
001			978-3-642-23250-3
003			DE-He213
005			20201213204015.0
007			cr nn 008mamaa
008			110914s2012 gw | s |||| 0|eng d
020			_a9783642232503 _9978-3-642-23250-3
024	7		_a10.1007/978-3-642-23250-3 _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		_aBenesty, Jacob. _eauthor.
245	1	0	_aSpeech Enhancement in the STFT Domain _h[electronic resource] / _cby Jacob Benesty, Jingdong Chen, Emanuël A.P. Habets.
264		1	_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg, _c2012.
300			_aVII, 109p. 5 illus. _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
505	0		_aIntroduction -- Single-Channel Speech Enhancement with a Gain -- Single-Channel Speech Enhancement with a Filter -- Multichannel Speech Enhancement with Gains -- Multichannel Speech Enhancement with Filters -- The Bifrequency Spectrum in Speech Enhancement -- Summary and Perspectives.
520			_aThis work addresses this problem in the short-time Fourier transform (STFT) domain. We divide the general problem into five basic categories depending on the number of microphones being used and whether the interframe or interband correlation is considered. The first category deals with the single-channel problem where STFT coefficients at different frames and frequency bands are assumed to be independent. In this case, the noise reduction filter in each frequency band is basically a real gain. Since a gain does not improve the signal-to-noise ratio (SNR) for any given subband and frame, the noise reduction is basically achieved by liftering the subbands and frames that are less noisy while weighing down on those that are more noisy. The second category also concerns the single-channel problem. The difference is that now the interframe correlation is taken into account and a filter is applied in each subband instead of just a gain. The advantage of using the interframe correlation is that we can improve not only the long-time fullband SNR, but the frame-wise subband SNR as well. The third and fourth classes discuss the problem of multichannel noise reduction in the STFT domain with and without interframe correlation, respectively. In the last category, we consider the interband correlation in the design of the noise reduction filters. We illustrate the basic principle for the single-channel case as an example, while this concept can be generalized to other scenarios. In all categories, we propose different optimization cost functions from which we derive the optimal filters and we also define the performance measures that help analyzing them.
650		0	_aEngineering.
650		0	_aComputer science.
650		0	_aFourier analysis.
650		0	_aAcoustics in engineering.
650	1	4	_aEngineering.
650	2	4	_aSignal, Image and Speech Processing.
650	2	4	_aFourier Analysis.
650	2	4	_aEngineering Acoustics.
650	2	4	_aModels and Principles.
700	1		_aChen, Jingdong. _eauthor.
700	1		_aHabets, Emanuël A.P. _eauthor.
710	2		_aSpringerLink (Online service)
773	0		_tSpringer eBooks
776	0	8	_iPrinted edition: _z9783642232497
830		0	_aSpringerBriefs in Electrical and Computer Engineering
856	4	0	_uhttp://dx.doi.org/10.1007/978-3-642-23250-3
912			_aZDB-2-ENG
950			_aEngineering (Springer-11647)
999			_c23733 _d23733