Syntax-based rewriting for simultaneous machine translation

He He, Alvin Grissom, Jordan Boyd-Graber, Hal Daumé

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Divergent word order between languages causes delay in simultaneous machine translation. We present a sentence rewriting method that generates more monotonic translations to improve the speedaccuracy tradeoff. We design grammaticality and meaning-preserving syntactic transformation rules that operate on constituent parse trees. We apply the rules to reference translations to make their word order closer to the source language word order. On Japanese-English translation (two languages with substantially different structure), incorporating the rewritten, more monotonic reference translation into a phrase-based machine translation system enables better translations faster than a baseline system that only uses gold reference translations.

Original languageEnglish (US)
Title of host publicationConference Proceedings - EMNLP 2015
Subtitle of host publicationConference on Empirical Methods in Natural Language Processing
PublisherAssociation for Computational Linguistics (ACL)
Pages55-64
Number of pages10
ISBN (Electronic)9781941643327
DOIs
StatePublished - 2015
EventConference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Lisbon, Portugal
Duration: Sep 17 2015Sep 21 2015

Publication series

NameConference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing

Other

OtherConference on Empirical Methods in Natural Language Processing, EMNLP 2015
CountryPortugal
CityLisbon
Period9/17/159/21/15

ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Computer Science Applications
  • Information Systems

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  • Cite this

    He, H., Grissom, A., Boyd-Graber, J., & Daumé, H. (2015). Syntax-based rewriting for simultaneous machine translation. In Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing (pp. 55-64). (Conference Proceedings - EMNLP 2015: Conference on Empirical Methods in Natural Language Processing). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/d15-1006