@inproceedings{yang-etal-2019-sentence,
title = "Sentence-Level Agreement for Neural Machine Translation",
author = "Yang, Mingming and
Wang, Rui and
Chen, Kehai and
Utiyama, Masao and
Sumita, Eiichiro and
Zhang, Min and
Zhao, Tiejun",
editor = "Korhonen, Anna and
Traum, David and
M{\`a}rquez, Llu{\'\i}s",
booktitle = "Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics",
month = jul,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/P19-1296",
doi = "10.18653/v1/P19-1296",
pages = "3076--3082",
abstract = "The training objective of neural machine translation (NMT) is to minimize the loss between the words in the translated sentences and those in the references. In NMT, there is a natural correspondence between the source sentence and the target sentence. However, this relationship has only been represented using the entire neural network and the training objective is computed in word-level. In this paper, we propose a sentence-level agreement module to directly minimize the difference between the representation of source and target sentence. The proposed agreement module can be integrated into NMT as an additional training objective function and can also be used to enhance the representation of the source sentences. Empirical results on the NIST Chinese-to-English and WMT English-to-German tasks show the proposed agreement module can significantly improve the NMT performance.",
}
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<abstract>The training objective of neural machine translation (NMT) is to minimize the loss between the words in the translated sentences and those in the references. In NMT, there is a natural correspondence between the source sentence and the target sentence. However, this relationship has only been represented using the entire neural network and the training objective is computed in word-level. In this paper, we propose a sentence-level agreement module to directly minimize the difference between the representation of source and target sentence. The proposed agreement module can be integrated into NMT as an additional training objective function and can also be used to enhance the representation of the source sentences. Empirical results on the NIST Chinese-to-English and WMT English-to-German tasks show the proposed agreement module can significantly improve the NMT performance.</abstract>
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%0 Conference Proceedings
%T Sentence-Level Agreement for Neural Machine Translation
%A Yang, Mingming
%A Wang, Rui
%A Chen, Kehai
%A Utiyama, Masao
%A Sumita, Eiichiro
%A Zhang, Min
%A Zhao, Tiejun
%Y Korhonen, Anna
%Y Traum, David
%Y Màrquez, Lluís
%S Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics
%D 2019
%8 July
%I Association for Computational Linguistics
%C Florence, Italy
%F yang-etal-2019-sentence
%X The training objective of neural machine translation (NMT) is to minimize the loss between the words in the translated sentences and those in the references. In NMT, there is a natural correspondence between the source sentence and the target sentence. However, this relationship has only been represented using the entire neural network and the training objective is computed in word-level. In this paper, we propose a sentence-level agreement module to directly minimize the difference between the representation of source and target sentence. The proposed agreement module can be integrated into NMT as an additional training objective function and can also be used to enhance the representation of the source sentences. Empirical results on the NIST Chinese-to-English and WMT English-to-German tasks show the proposed agreement module can significantly improve the NMT performance.
%R 10.18653/v1/P19-1296
%U https://aclanthology.org/P19-1296
%U https://doi.org/10.18653/v1/P19-1296
%P 3076-3082
Markdown (Informal)
[Sentence-Level Agreement for Neural Machine Translation](https://aclanthology.org/P19-1296) (Yang et al., ACL 2019)
ACL
- Mingming Yang, Rui Wang, Kehai Chen, Masao Utiyama, Eiichiro Sumita, Min Zhang, and Tiejun Zhao. 2019. Sentence-Level Agreement for Neural Machine Translation. In Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics, pages 3076–3082, Florence, Italy. Association for Computational Linguistics.