The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018
Miguel Graça, Yunsu Kim, Julian Schamper, Jiahui Geng, Hermann Ney
Correct Metadata for
Abstract
This paper describes the unsupervised neural machine translation (NMT) systems of the RWTH Aachen University developed for the English ↔ German news translation task of the EMNLP 2018 Third Conference on Machine Translation (WMT 2018). Our work is based on iterative back-translation using a shared encoder-decoder NMT model. We extensively compare different vocabulary types, word embedding initialization schemes and optimization methods for our model. We also investigate gating and weight normalization for the word embedding layer.- Anthology ID:
- W18-6409
- Volume:
- Proceedings of the Third Conference on Machine Translation: Shared Task Papers
- Month:
- October
- Year:
- 2018
- Address:
- Belgium, Brussels
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Lucia Specia, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 377–385
- Language:
- URL:
- https://aclanthology.org/W18-6409/
- DOI:
- 10.18653/v1/W18-6409
- Bibkey:
- Cite (ACL):
- Miguel Graça, Yunsu Kim, Julian Schamper, Jiahui Geng, and Hermann Ney. 2018. The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 377–385, Belgium, Brussels. Association for Computational Linguistics.
- Cite (Informal):
- The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018 (Graça et al., WMT 2018)
- Copy Citation:
- PDF:
- https://aclanthology.org/W18-6409.pdf
Export citation
@inproceedings{graca-etal-2018-rwth,
    title = "The {RWTH} {A}achen {U}niversity {E}nglish-{G}erman and {G}erman-{E}nglish Unsupervised Neural Machine Translation Systems for {WMT} 2018",
    author = "Gra{\c{c}}a, Miguel  and
      Kim, Yunsu  and
      Schamper, Julian  and
      Geng, Jiahui  and
      Ney, Hermann",
    editor = "Bojar, Ond{\v{r}}ej  and
      Chatterjee, Rajen  and
      Federmann, Christian  and
      Fishel, Mark  and
      Graham, Yvette  and
      Haddow, Barry  and
      Huck, Matthias  and
      Yepes, Antonio Jimeno  and
      Koehn, Philipp  and
      Monz, Christof  and
      Negri, Matteo  and
      N{\'e}v{\'e}ol, Aur{\'e}lie  and
      Neves, Mariana  and
      Post, Matt  and
      Specia, Lucia  and
      Turchi, Marco  and
      Verspoor, Karin",
    booktitle = "Proceedings of the Third Conference on Machine Translation: Shared Task Papers",
    month = oct,
    year = "2018",
    address = "Belgium, Brussels",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W18-6409/",
    doi = "10.18653/v1/W18-6409",
    pages = "377--385",
    abstract = "This paper describes the unsupervised neural machine translation (NMT) systems of the RWTH Aachen University developed for the English {\ensuremath{\leftrightarrow}} German news translation task of the \textit{EMNLP 2018 Third Conference on Machine Translation} (WMT 2018). Our work is based on iterative back-translation using a shared encoder-decoder NMT model. We extensively compare different vocabulary types, word embedding initialization schemes and optimization methods for our model. We also investigate gating and weight normalization for the word embedding layer."
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%0 Conference Proceedings %T The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018 %A Graça, Miguel %A Kim, Yunsu %A Schamper, Julian %A Geng, Jiahui %A Ney, Hermann %Y Bojar, Ondřej %Y Chatterjee, Rajen %Y Federmann, Christian %Y Fishel, Mark %Y Graham, Yvette %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Monz, Christof %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Post, Matt %Y Specia, Lucia %Y Turchi, Marco %Y Verspoor, Karin %S Proceedings of the Third Conference on Machine Translation: Shared Task Papers %D 2018 %8 October %I Association for Computational Linguistics %C Belgium, Brussels %F graca-etal-2018-rwth %X This paper describes the unsupervised neural machine translation (NMT) systems of the RWTH Aachen University developed for the English \ensuremathłeftrightarrow German news translation task of the EMNLP 2018 Third Conference on Machine Translation (WMT 2018). Our work is based on iterative back-translation using a shared encoder-decoder NMT model. We extensively compare different vocabulary types, word embedding initialization schemes and optimization methods for our model. We also investigate gating and weight normalization for the word embedding layer. %R 10.18653/v1/W18-6409 %U https://aclanthology.org/W18-6409/ %U https://doi.org/10.18653/v1/W18-6409 %P 377-385
Markdown (Informal)
[The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018](https://aclanthology.org/W18-6409/) (Graça et al., WMT 2018)
- The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018 (Graça et al., WMT 2018)
ACL
- Miguel Graça, Yunsu Kim, Julian Schamper, Jiahui Geng, and Hermann Ney. 2018. The RWTH Aachen University English-German and German-English Unsupervised Neural Machine Translation Systems for WMT 2018. In Proceedings of the Third Conference on Machine Translation: Shared Task Papers, pages 377–385, Belgium, Brussels. Association for Computational Linguistics.