000 | 03074nam a22005775i 4500 | ||
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001 | 978-3-642-34425-1 | ||
003 | DE-He213 | ||
005 | 20200421112035.0 | ||
007 | cr nn 008mamaa | ||
008 | 121026s2013 gw | s |||| 0|eng d | ||
020 |
_a9783642344251 _9978-3-642-34425-1 |
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024 | 7 |
_a10.1007/978-3-642-34425-1 _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 |
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082 | 0 | 4 |
_a621.382 _223 |
100 | 1 |
_aVasquez, Daniel. _eauthor. |
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245 | 1 | 0 |
_aHierarchical Neural Network Structures for Phoneme Recognition _h[electronic resource] / _cby Daniel Vasquez, Rainer Gruhn, Wolfgang Minker. |
264 | 1 |
_aBerlin, Heidelberg : _bSpringer Berlin Heidelberg : _bImprint: Springer, _c2013. |
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300 |
_aXVIII, 134 p. _bonline resource. |
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336 |
_atext _btxt _2rdacontent |
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337 |
_acomputer _bc _2rdamedia |
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338 |
_aonline resource _bcr _2rdacarrier |
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347 |
_atext file _bPDF _2rda |
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490 | 1 |
_aSignals and Communication Technology, _x1860-4862 |
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505 | 0 | _aBackground in Speech Recognition -- Phoneme Recognition Task -- Hierarchical Approach and Downsampling Schemes -- Extending the Hierarchical Scheme: Inter and Intra Phonetic Information -- Theoretical framework for phoneme recognition analysis. | |
520 | _aIn this book, hierarchical structures based on neural networks are investigated for automatic speech recognition. These structures are evaluated on the phoneme recognition task where a Hybrid Hidden Markov Model/Artificial Neural Network paradigm is used. The baseline hierarchical scheme consists of two levels each which is based on a Multilayered Perceptron. Additionally, the output of the first level serves as a second level input. The computational speed of the phoneme recognizer can be substantially increased by removing redundant information still contained at the first level output. Several techniques based on temporal and phonetic criteria have been investigated to remove this redundant information. The computational time could be reduced by 57% whilst keeping the system accuracy comparable to the baseline hierarchical approach. | ||
650 | 0 | _aEngineering. | |
650 | 0 | _aUser interfaces (Computer systems). | |
650 | 0 | _aComputational linguistics. | |
650 | 0 | _aComputational intelligence. | |
650 | 1 | 4 | _aEngineering. |
650 | 2 | 4 | _aSignal, Image and Speech Processing. |
650 | 2 | 4 | _aUser Interfaces and Human Computer Interaction. |
650 | 2 | 4 | _aComputational Intelligence. |
650 | 2 | 4 | _aLanguage Translation and Linguistics. |
700 | 1 |
_aGruhn, Rainer. _eauthor. |
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700 | 1 |
_aMinker, Wolfgang. _eauthor. |
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710 | 2 | _aSpringerLink (Online service) | |
773 | 0 | _tSpringer eBooks | |
776 | 0 | 8 |
_iPrinted edition: _z9783642344244 |
830 | 0 |
_aSignals and Communication Technology, _x1860-4862 |
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856 | 4 | 0 | _uhttp://dx.doi.org/10.1007/978-3-642-34425-1 |
912 | _aZDB-2-ENG | ||
942 | _cEBK | ||
999 |
_c56337 _d56337 |