@inproceedings{pham-etal-2020-priming,
title = "Priming Neural Machine Translation",
author = "Pham, Minh Quang and
Xu, Jitao and
Crego, Josep and
Yvon, Fran{\c{c}}ois and
Senellart, Jean",
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.63",
pages = "516--527",
abstract = "Priming is a well known and studied psychology phenomenon based on the prior presentation of one stimulus (cue) to influence the processing of a response. In this paper, we propose a framework to mimic the process of priming in the context of neural machine translation (NMT). We evaluate the effect of using similar translations as priming cues on the NMT network. We propose a method to inject priming cues into the NMT network and compare our framework to other mechanisms that perform micro-adaptation during inference. Overall, experiments conducted in a multi-domain setting confirm that adding priming cues in the NMT decoder can go a long way towards improving the translation accuracy. Besides, we show the suitability of our framework to gather valuable information for an NMT network from monolingual resources.",
}
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%0 Conference Proceedings
%T Priming Neural Machine Translation
%A Pham, Minh Quang
%A Xu, Jitao
%A Crego, Josep
%A Yvon, François
%A Senellart, Jean
%S Proceedings of the Fifth Conference on Machine Translation
%D 2020
%8 nov
%I Association for Computational Linguistics
%C Online
%F pham-etal-2020-priming
%X Priming is a well known and studied psychology phenomenon based on the prior presentation of one stimulus (cue) to influence the processing of a response. In this paper, we propose a framework to mimic the process of priming in the context of neural machine translation (NMT). We evaluate the effect of using similar translations as priming cues on the NMT network. We propose a method to inject priming cues into the NMT network and compare our framework to other mechanisms that perform micro-adaptation during inference. Overall, experiments conducted in a multi-domain setting confirm that adding priming cues in the NMT decoder can go a long way towards improving the translation accuracy. Besides, we show the suitability of our framework to gather valuable information for an NMT network from monolingual resources.
%U https://aclanthology.org/2020.wmt-1.63
%P 516-527
Markdown (Informal)
[Priming Neural Machine Translation](https://aclanthology.org/2020.wmt-1.63) (Pham et al., WMT 2020)
ACL
- Minh Quang Pham, Jitao Xu, Josep Crego, François Yvon, and Jean Senellart. 2020. Priming Neural Machine Translation. In Proceedings of the Fifth Conference on Machine Translation, pages 516–527, Online. Association for Computational Linguistics.