Docent: A Document-Level Decoder for Phrase-Based Statistical Machine Translation
2013 (English)In: Proceedings of the 51st Annual Meeting of the Association for Computational Linguistics: System Demonstrations, Association for Computational Linguistics, 2013, 193-198 p.Conference paper (Refereed)
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.
Place, publisher, year, edition, pages
Association for Computational Linguistics, 2013. 193-198 p.
Language Technology (Computational Linguistics)
Research subject Computational Linguistics
IdentifiersURN: urn:nbn:se:uu:diva-207690OAI: oai:DiVA.org:uu-207690DiVA: diva2:649088
ACL 2013 (51st Annual Meeting of the Association for Computational Linguistics); 4-9 August 2013; Sofia, Bulgaria