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