Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations

Sameen Maruf; André F. T. Martins; Gholamreza Haffari

doi:10.18653/v1/W18-6311

Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations

Sameen Maruf, André F. T. Martins, Gholamreza Haffari

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Abstract

Recent works in neural machine translation have begun to explore document translation. However, translating online multi-speaker conversations is still an open problem. In this work, we propose the task of translating Bilingual Multi-Speaker Conversations, and explore neural architectures which exploit both source and target-side conversation histories for this task. To initiate an evaluation for this task, we introduce datasets extracted from Europarl v7 and OpenSubtitles2016. Our experiments on four language-pairs confirm the significance of leveraging conversation history, both in terms of BLEU and manual evaluation.

Anthology ID:: W18-6311
Volume:: Proceedings of the Third Conference on Machine Translation: Research Papers
Month:: October
Year:: 2018
Address:: Brussels, Belgium
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:: 101–112
Language:
URL:: https://aclanthology.org/W18-6311/
DOI:: 10.18653/v1/W18-6311
Bibkey:
Cite (ACL):: Sameen Maruf, André F. T. Martins, and Gholamreza Haffari. 2018. Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 101–112, Brussels, Belgium. Association for Computational Linguistics.
Cite (Informal):: Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations (Maruf et al., WMT 2018)
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PDF:: https://aclanthology.org/W18-6311.pdf

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@inproceedings{maruf-etal-2018-contextual,
    title = "Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations",
    author = "Maruf, Sameen  and
      Martins, Andr{\'e} F. T.  and
      Haffari, Gholamreza",
    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: Research Papers",
    month = oct,
    year = "2018",
    address = "Brussels, Belgium",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/W18-6311/",
    doi = "10.18653/v1/W18-6311",
    pages = "101--112",
    abstract = "Recent works in neural machine translation have begun to explore document translation. However, translating online multi-speaker conversations is still an open problem. In this work, we propose the task of translating Bilingual Multi-Speaker Conversations, and explore neural architectures which exploit both source and target-side conversation histories for this task. To initiate an evaluation for this task, we introduce datasets extracted from Europarl v7 and OpenSubtitles2016. Our experiments on four language-pairs confirm the significance of leveraging conversation history, both in terms of BLEU and manual evaluation."
}

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%0 Conference Proceedings
%T Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations
%A Maruf, Sameen
%A Martins, André F. T.
%A Haffari, Gholamreza
%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: Research Papers
%D 2018
%8 October
%I Association for Computational Linguistics
%C Brussels, Belgium
%F maruf-etal-2018-contextual
%X Recent works in neural machine translation have begun to explore document translation. However, translating online multi-speaker conversations is still an open problem. In this work, we propose the task of translating Bilingual Multi-Speaker Conversations, and explore neural architectures which exploit both source and target-side conversation histories for this task. To initiate an evaluation for this task, we introduce datasets extracted from Europarl v7 and OpenSubtitles2016. Our experiments on four language-pairs confirm the significance of leveraging conversation history, both in terms of BLEU and manual evaluation.
%R 10.18653/v1/W18-6311
%U https://aclanthology.org/W18-6311/
%U https://doi.org/10.18653/v1/W18-6311
%P 101-112

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Markdown (Informal)

[Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations](https://aclanthology.org/W18-6311/) (Maruf et al., WMT 2018)

Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations (Maruf et al., WMT 2018)

ACL

Sameen Maruf, André F. T. Martins, and Gholamreza Haffari. 2018. Contextual Neural Model for Translating Bilingual Multi-Speaker Conversations. In Proceedings of the Third Conference on Machine Translation: Research Papers, pages 101–112, Brussels, Belgium. Association for Computational Linguistics.