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The Edinburgh/JHU Phrase-based Machine Translation Systems for WMT~2015

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Haddow, Barry, Huck, Matthias, Birch, Alexandra, Bogoychev, Nikolay, Koehn, Philipp·2015·Proceedings of the Tenth Workshop on Statistical Machine Translation
DOI 10.18653/v1/w15-3013
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Abstract

This paper describes the submission of the University of Edinburgh and the Johns Hopkins University for the shared translation task of the EMNLP 2015 Tenth Workshop on Statistical Machine Translation (WMT 2015).We set up phrase-based statistical machine translation systems for all ten language pairs of this year's evaluation campaign, which are English paired with Czech, Finnish, French, German, and Russian in both translation directions.Novel research directions we investigated include: neural network language models and bilingual neural network language models, a comprehensive use of word classes, and sparse lexicalized reordering features.

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  • The phrase-based system by Haddow et al. (2015) outperforms our WDict baseline by 1.5 BLEU for English→Russian.

    “It outperforms our WDict baseline by 1.5 BLEU.”

    From Neural Machine Translation of Rare Words with Subword Units (2016) · cites this paper as Haddow et al. (2015)

  • For English→Russian, the state of the art is the phrase-based system by Haddow et al. (2015).

    “For English→Russian, the state of the art is the phrase-based system by Haddow et al. (2015).”

    From Neural Machine Translation of Rare Words with Subword Units (2016) · cites this paper as Haddow et al. (2015)

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Research works printed but not linked: 33

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Metadata

Authors
Haddow, B., Huck, M., Birch, A., Bogoychev, N., & Koehn, P.
Affiliations
  • University of Edinburgh (GB)
  • Johns Hopkins University (US)
ORCID
Venue
Proceedings of the Tenth Workshop on Statistical Machine Translation
Publisher
Association for Computational Linguistics
Published
2015
Pages
126-133
DOI
10.18653/v1/w15-3013
OpenAlex
W2528305545
Cited by
14
References
0
Citations by year
2022: 1 · 2021: 1 · 2018: 2 · 2017: 1 · 2016: 7 · 2015: 2
FWCI
2.15
Type
conference paper
Language
en
Open access
Licence
cc-by
Locations
  • Conference on Machine Translation (WMT) (publishedVersion, cc-by)
  • RWTH Publications (RWTH Aachen) (submittedVersion, cc-by)
  • Edinburgh Research Explorer (University of Edinburgh) (submittedVersion, other-oa)
Funders
European Commission (644333, 645452, 644402, 645487)
Topics
  • Physical Sciences › Computer Science › Artificial Intelligence › Natural Language Processing Techniques
  • Physical Sciences › Computer Science › Artificial Intelligence › Speech Recognition and Synthesis
  • Physical Sciences › Computer Science › Artificial Intelligence › Topic Modeling
Keywords
phrase-based statistical machine translation, neural language models, parts of speech, English-Czech translation, English-French translation, English-German translation, English-Russian translation, English-Finnish translation

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