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020 _a9789813297487
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024 7 _a10.1007/978-981-32-9748-7
_2doi
050 4 _aQA76.9.N38
072 7 _aUYQL
_2bicssc
072 7 _aCOM073000
_2bisacsh
072 7 _aUYQL
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082 0 4 _a006.35
_223
100 1 _aCheng, Yong.
_eauthor.
_4aut
_4http://id.loc.gov/vocabulary/relators/aut
245 1 0 _aJoint Training for Neural Machine Translation
_h[electronic resource] /
_cby Yong Cheng.
250 _a1st ed. 2019.
264 1 _aSingapore :
_bSpringer Nature Singapore :
_bImprint: Springer,
_c2019.
300 _aXIII, 78 p. 23 illus., 9 illus. in color.
_bonline resource.
336 _atext
_btxt
_2rdacontent
337 _acomputer
_bc
_2rdamedia
338 _aonline resource
_bcr
_2rdacarrier
347 _atext file
_bPDF
_2rda
490 1 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5061
505 0 _a1. Introduction -- 2. Neural Machine Translation -- 3. Agreement-based Joint Training for Bidirectional Attention-based Neural Machine Translation -- 4. Semi-supervised Learning for Neural Machine Translation -- 5. Joint Training for Pivot-based Neural Machine Translation -- 6. Joint Modeling for Bidirectional Neural Machine Translation with Contrastive Learning -- 7. Related Work -- 8. Conclusion.
520 _aThis book presents four approaches to jointly training bidirectional neural machine translation (NMT) models. First, in order to improve the accuracy of the attention mechanism, it proposes an agreement-based joint training approach to help the two complementary models agree on word alignment matrices for the same training data. Second, it presents a semi-supervised approach that uses an autoencoder to reconstruct monolingual corpora, so as to incorporate these corpora into neural machine translation. It then introduces a joint training algorithm for pivot-based neural machine translation, which can be used to mitigate the data scarcity problem. Lastly it describes an end-to-end bidirectional NMT model to connect the source-to-target and target-to-source translation models, allowing the interaction of parameters between these two directional models.
650 0 _aNatural language processing (Computer science).
650 0 _aLogic programming.
650 1 4 _aNatural Language Processing (NLP).
650 2 4 _aLogic in AI.
710 2 _aSpringerLink (Online service)
773 0 _tSpringer Nature eBook
776 0 8 _iPrinted edition:
_z9789813297470
776 0 8 _iPrinted edition:
_z9789813297494
830 0 _aSpringer Theses, Recognizing Outstanding Ph.D. Research,
_x2190-5061
856 4 0 _uhttps://doi.org/10.1007/978-981-32-9748-7
912 _aZDB-2-SCS
912 _aZDB-2-SXCS
942 _cSPRINGER
999 _c174285
_d174285