000 | 03117nam a22005535i 4500 | ||
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001 | 978-1-4614-6360-3 | ||
003 | DE-He213 | ||
005 | 20200421112038.0 | ||
007 | cr nn 008mamaa | ||
008 | 130125s2013 xxu| s |||| 0|eng d | ||
020 |
_a9781461463603 _9978-1-4614-6360-3 |
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024 | 7 |
_a10.1007/978-1-4614-6360-3 _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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_aUYS _2bicssc |
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_aTEC008000 _2bisacsh |
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072 | 7 |
_aCOM073000 _2bisacsh |
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082 | 0 | 4 |
_a621.382 _223 |
100 | 1 |
_aRao, K. Sreenivasa. _eauthor. |
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245 | 1 | 0 |
_aRobust Emotion Recognition using Spectral and Prosodic Features _h[electronic resource] / _cby K. Sreenivasa Rao, Shashidhar G. Koolagudi. |
264 | 1 |
_aNew York, NY : _bSpringer New York : _bImprint: Springer, _c2013. |
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300 |
_aXII, 118 p. 37 illus., 15 illus. in color. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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_acomputer _bc _2rdamedia |
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_aonline resource _bcr _2rdacarrier |
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_atext file _bPDF _2rda |
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490 | 1 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
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505 | 0 | _aIntroduction -- Robust Emotion Recognition using Pitch Synchronous and Sub-syllabic Spectral Features -- Robust Emotion Recognition using Word and Syllable Level Prosodic Features -- Robust Emotion Recognition using Combination of Excitation Source, Spectral and Prosodic Features -- Robust Emotion Recognition using Speaking Rate Features -- Emotion Recognition on Real Life Emotions -- Summary and Conclusions -- MFCC Features -- Gaussian Mixture Model (GMM). | |
520 | _aIn this brief, the authors discuss recently explored spectral (sub-segmental and pitch synchronous) and prosodic (global and local features at word and syllable levels in different parts of the utterance) features for discerning emotions in a robust manner. The authors also delve into the complementary evidences obtained from excitation source, vocal tract system and prosodic features for the purpose of enhancing emotion recognition performance. Features based on speaking rate characteristics are explored with the help of multi-stage and hybrid models for further improving emotion recognition performance. Proposed spectral and prosodic features are evaluated on real life emotional speech corpus. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aUser interfaces (Computer systems). | |
650 | 0 | _aComputational linguistics. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aSignal, Image and Speech Processing. |
650 | 2 | 4 | _aUser Interfaces and Human Computer Interaction. |
650 | 2 | 4 | _aLanguage Translation and Linguistics. |
650 | 2 | 4 | _aComputational Linguistics. |
700 | 1 |
_aKoolagudi, Shashidhar G. _eauthor. |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9781461463597 |
830 | 0 |
_aSpringerBriefs in Electrical and Computer Engineering, _x2191-8112 |
|
856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-1-4614-6360-3 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c56460 _d56460 |