000 | 03836nam a22005535i 4500 | ||
---|---|---|---|
001 | 978-3-031-02164-0 | ||
003 | DE-He213 | ||
005 | 20240730165213.0 | ||
007 | cr nn 008mamaa | ||
008 | 220601s2016 sz | s |||| 0|eng d | ||
020 |
_a9783031021640 _9978-3-031-02164-0 |
||
024 | 7 |
_a10.1007/978-3-031-02164-0 _2doi |
|
050 | 4 | _aQ334-342 | |
050 | 4 | _aTA347.A78 | |
072 | 7 |
_aUYQ _2bicssc |
|
072 | 7 |
_aCOM004000 _2bisacsh |
|
072 | 7 |
_aUYQ _2thema |
|
082 | 0 | 4 |
_a006.3 _223 |
100 | 1 |
_aWilliams, Philip. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987840 |
|
245 | 1 | 0 |
_aSyntax-based Statistical Machine Translation _h[electronic resource] / _cby Philip Williams, Rico Sennrich, Matt Post, Philipp Koehn. |
250 | _a1st ed. 2016. | ||
264 | 1 |
_aCham : _bSpringer International Publishing : _bImprint: Springer, _c2016. |
|
300 |
_aXVIII, 190 p. _bonline resource. |
||
336 |
_atext _btxt _2rdacontent |
||
337 |
_acomputer _bc _2rdamedia |
||
338 |
_aonline resource _bcr _2rdacarrier |
||
347 |
_atext file _bPDF _2rda |
||
490 | 1 |
_aSynthesis Lectures on Human Language Technologies, _x1947-4059 |
|
505 | 0 | _aPreface -- Acknowledgments -- Models -- Learning from Parallel Text -- Decoding I: Preliminaries -- Decoding II: Tree Decoding -- Decoding III: String Decoding -- Selected Topics -- Closing Remarks -- Bibliography -- Authors' Biographies -- Author Index -- Index. | |
520 | _aThis unique book provides a comprehensive introduction to the most popular syntax-based statistical machine translation models, filling a gap in the current literature for researchers and developers in human language technologies. While phrase-based models have previously dominated the field, syntax-based approaches have proved a popular alternative, as they elegantly solve many of the shortcomings of phrase-based models. The heart of this book is a detailed introduction to decoding for syntax-based models. The book begins with an overview of synchronous-context free grammar (SCFG) and synchronous tree-substitution grammar (STSG) along with their associated statistical models. It also describes how three popular instantiations (Hiero, SAMT, and GHKM) are learned from parallel corpora. It introduces and details hypergraphs and associated general algorithms, as well as algorithms for decoding with both tree and string input. Special attention is given to efficiency, includingsearch approximations such as beam search and cube pruning, data structures, and parsing algorithms. The book consistently highlights the strengths (and limitations) of syntax-based approaches, including their ability to generalize phrase-based translation units, their modeling of specific linguistic phenomena, and their function of structuring the search space. | ||
650 | 0 |
_aArtificial intelligence. _93407 |
|
650 | 0 |
_aNatural language processing (Computer science). _94741 |
|
650 | 0 |
_aComputational linguistics. _96146 |
|
650 | 1 | 4 |
_aArtificial Intelligence. _93407 |
650 | 2 | 4 |
_aNatural Language Processing (NLP). _931587 |
650 | 2 | 4 |
_aComputational Linguistics. _96146 |
700 | 1 |
_aSennrich, Rico. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987842 |
|
700 | 1 |
_aPost, Matt. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987844 |
|
700 | 1 |
_aKoehn, Philipp. _eauthor. _4aut _4http://id.loc.gov/vocabulary/relators/aut _987845 |
|
710 | 2 |
_aSpringerLink (Online service) _987847 |
|
773 | 0 | _tSpringer Nature eBook | |
776 | 0 | 8 |
_iPrinted edition: _z9783031010361 |
776 | 0 | 8 |
_iPrinted edition: _z9783031032929 |
830 | 0 |
_aSynthesis Lectures on Human Language Technologies, _x1947-4059 _987849 |
|
856 | 4 | 0 | _uhttps://doi.org/10.1007/978-3-031-02164-0 |
912 | _aZDB-2-SXSC | ||
942 | _cEBK | ||
999 |
_c86158 _d86158 |