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)
- Copy Citation:
- PDF:
- https://aclanthology.org/W18-6311.pdf
- Code
- sameenmaruf/Bi-MSMT
- Data
- OpenSubtitles
Export citation
@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
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.