| 000 | 02666nam a22004935i 4500 | ||
|---|---|---|---|
| 001 | 978-3-319-07130-5 | ||
| 003 | DE-He213 | ||
| 005 | 20200421111200.0 | ||
| 007 | cr nn 008mamaa | ||
| 008 | 140621s2014 gw | s |||| 0|eng d | ||
| 020 |
_a9783319071305 _9978-3-319-07130-5 |
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| 024 | 7 |
_a10.1007/978-3-319-07130-5 _2doi |
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| 050 | 4 | _aTK5102.9 | |
| 050 | 4 | _aTA1637-1638 | |
| 050 | 4 | _aTK7882.S65 | |
| 072 | 7 |
_aTTBM _2bicssc |
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| 072 | 7 |
_aUYS _2bicssc |
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| 072 | 7 |
_aTEC008000 _2bisacsh |
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| 072 | 7 |
_aCOM073000 _2bisacsh |
|
| 082 | 0 | 4 |
_a621.382 _223 |
| 100 | 1 |
_aRao, K. Sreenivasa. _eauthor. |
|
| 245 | 1 | 0 |
_aRobust Speaker Recognition in Noisy Environments _h[electronic resource] / _cby K. Sreenivasa Rao, Sourjya Sarkar. |
| 264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2014. |
|
| 300 |
_aXII, 139 p. 31 illus., 25 illus. in color. _bonline resource. |
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| 336 |
_atext _btxt _2rdacontent |
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| 337 |
_acomputer _bc _2rdamedia |
||
| 338 |
_aonline resource _bcr _2rdacarrier |
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| 347 |
_atext file _bPDF _2rda |
||
| 490 | 1 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
| 505 | 0 | _aRobust Speaker Verification - A Review -- Speaker Verification in Noisy Environments using Gaussian Mixture Models -- Stochastic Feature Compensation for Robust Speaker Verification -- Robust Speaker Modeling for Speaker Verification in Noisy Environments. | |
| 520 | _aThis book discusses speaker recognition methods to deal with realistic variable noisy environments. The text covers authentication systems for; robust noisy background environments, functions in real time and incorporated in mobile devices. The book focuses on different approaches to enhance the accuracy of speaker recognition in presence of varying background environments. The authors examine: (a) Feature compensation using multiple background models, (b) Feature mapping using data-driven stochastic models, (c) Design of super vector- based GMM-SVM framework for robust speaker recognition, (d) Total variability modeling (i-vectors) in a discriminative framework and (e) Boosting method to fuse evidences from multiple SVM models. | ||
| 650 | 0 | _aEngineering. | |
| 650 | 1 | 4 | _aEngineering. |
| 650 | 2 | 4 | _aSignal, Image and Speech Processing. |
| 700 | 1 |
_aSarkar, Sourjya. _eauthor. |
|
| 710 | 2 | _aSpringerLink (Online service) | |
| 773 | 0 | _tSpringer eBooks | |
| 776 | 0 | 8 |
_iPrinted edition: _z9783319071299 |
| 830 | 0 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
| 856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-319-07130-5 |
| 912 | _aZDB-2-ENG | ||
| 942 | _cEBK | ||
| 999 |
_c53787 _d53787 |
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