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Abstract
Simultaneous translation is a task in which translation begins before the speaker has finished speaking, so it is important to decide when to start the translation process. However, deciding whether to read more input words or start to translate is difficult for language pairs with different word orders such as English and Japanese. Motivated by the concept of pre-reordering, we propose a couple of simple decision rules using the label of the next constituent predicted by incremental constituent label prediction. In experiments on English-to-Japanese simultaneous translation, the proposed method outperformed baselines in the quality-latency trade-off.- Anthology ID:
- 2021.wmt-1.120
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Editors:
- Loic Barrault, Ondrej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussa, Christian Federmann, Mark Fishel, Alexander Fraser, Markus Freitag, Yvette Graham, Roman Grundkiewicz, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, Tom Kocmi, Andre Martins, Makoto Morishita, Christof Monz
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 1124–1134
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.120/
- DOI:
- Bibkey:
- Cite (ACL):
- Yasumasa Kano, Katsuhito Sudoh, and Satoshi Nakamura. 2021. Simultaneous Neural Machine Translation with Constituent Label Prediction. In Proceedings of the Sixth Conference on Machine Translation, pages 1124–1134, Online. Association for Computational Linguistics.
- Cite (Informal):
- Simultaneous Neural Machine Translation with Constituent Label Prediction (Kano et al., WMT 2021)
- Copy Citation:
- PDF:
- https://aclanthology.org/2021.wmt-1.120.pdf
- Video:
- https://aclanthology.org/2021.wmt-1.120.mp4
Export citation
@inproceedings{kano-etal-2021-simultaneous,
title = "Simultaneous Neural Machine Translation with Constituent Label Prediction",
author = "Kano, Yasumasa and
Sudoh, Katsuhito and
Nakamura, Satoshi",
editor = "Barrault, Loic and
Bojar, Ondrej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-jussa, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Freitag, Markus and
Graham, Yvette and
Grundkiewicz, Roman and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Kocmi, Tom and
Martins, Andre and
Morishita, Makoto and
Monz, Christof",
booktitle = "Proceedings of the Sixth Conference on Machine Translation",
month = nov,
year = "2021",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2021.wmt-1.120/",
pages = "1124--1134",
abstract = "Simultaneous translation is a task in which translation begins before the speaker has finished speaking, so it is important to decide when to start the translation process. However, deciding whether to read more input words or start to translate is difficult for language pairs with different word orders such as English and Japanese. Motivated by the concept of pre-reordering, we propose a couple of simple decision rules using the label of the next constituent predicted by incremental constituent label prediction. In experiments on English-to-Japanese simultaneous translation, the proposed method outperformed baselines in the quality-latency trade-off."
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%0 Conference Proceedings %T Simultaneous Neural Machine Translation with Constituent Label Prediction %A Kano, Yasumasa %A Sudoh, Katsuhito %A Nakamura, Satoshi %Y Barrault, Loic %Y Bojar, Ondrej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussa, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Freitag, Markus %Y Graham, Yvette %Y Grundkiewicz, Roman %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Kocmi, Tom %Y Martins, Andre %Y Morishita, Makoto %Y Monz, Christof %S Proceedings of the Sixth Conference on Machine Translation %D 2021 %8 November %I Association for Computational Linguistics %C Online %F kano-etal-2021-simultaneous %X Simultaneous translation is a task in which translation begins before the speaker has finished speaking, so it is important to decide when to start the translation process. However, deciding whether to read more input words or start to translate is difficult for language pairs with different word orders such as English and Japanese. Motivated by the concept of pre-reordering, we propose a couple of simple decision rules using the label of the next constituent predicted by incremental constituent label prediction. In experiments on English-to-Japanese simultaneous translation, the proposed method outperformed baselines in the quality-latency trade-off. %U https://aclanthology.org/2021.wmt-1.120/ %P 1124-1134
Markdown (Informal)
[Simultaneous Neural Machine Translation with Constituent Label Prediction](https://aclanthology.org/2021.wmt-1.120/) (Kano et al., WMT 2021)
- Simultaneous Neural Machine Translation with Constituent Label Prediction (Kano et al., WMT 2021)
ACL
- Yasumasa Kano, Katsuhito Sudoh, and Satoshi Nakamura. 2021. Simultaneous Neural Machine Translation with Constituent Label Prediction. In Proceedings of the Sixth Conference on Machine Translation, pages 1124–1134, Online. Association for Computational Linguistics.