Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation

Christian Hardmeier; Sara Stymne; Jörg Tiedemann; Joakim Nivre

Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation

Christian Hardmeier, Sara Stymne, Jörg Tiedemann, Joakim Nivre

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

Abstract

We describe Docent, an open-source decoder for statistical machine translation that breaks with the usual sentence-by-sentence paradigm and translates complete documents as units. By taking translation to the document level, our decoder can handle feature models with arbitrary discourse-wide dependencies and constitutes an essential infrastructure component in the quest for discourse-aware SMT models.

Originalsprog	Engelsk
Titel	Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations
Publikationsdato	9 aug. 2013
Status	Udgivet - 9 aug. 2013
Udgivet eksternt	Ja

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https://www.diva-portal.org/smash/get/diva2:649088/fulltext01.pdf

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title = "Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation",

abstract = "We describe Docent, an open-source decoder for statistical machine translation that breaks with the usual sentence-by-sentence paradigm and translates complete documents as units. By taking translation to the document level, our decoder can handle feature models with arbitrary discourse-wide dependencies and constitutes an essential infrastructure component in the quest for discourse-aware SMT models.",

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Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation. / Hardmeier, Christian; Stymne, Sara; Tiedemann, Jörg et al.
Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations. 2013.

Publikation: Konference artikel i Proceeding eller bog/rapport kapitel › Konferencebidrag i proceedings › Forskning › peer review

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AU - Hardmeier, Christian

AU - Stymne, Sara

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AU - Nivre, Joakim

PY - 2013/8/9

Y1 - 2013/8/9

N2 - We describe Docent, an open-source decoder for statistical machine translation that breaks with the usual sentence-by-sentence paradigm and translates complete documents as units. By taking translation to the document level, our decoder can handle feature models with arbitrary discourse-wide dependencies and constitutes an essential infrastructure component in the quest for discourse-aware SMT models.

AB - We describe Docent, an open-source decoder for statistical machine translation that breaks with the usual sentence-by-sentence paradigm and translates complete documents as units. By taking translation to the document level, our decoder can handle feature models with arbitrary discourse-wide dependencies and constitutes an essential infrastructure component in the quest for discourse-aware SMT models.

M3 - Article in proceedings

BT - Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations

ER -

Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation

Abstract

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