@inproceedings{chen-etal-2020-character,
title = "Character Mapping and Ad-hoc Adaptation: {E}dinburgh{'}s {IWSLT} 2020 Open Domain Translation System",
author = "Chen, Pinzhen and
Bogoychev, Nikolay and
Germann, Ulrich",
editor = {Federico, Marcello and
Waibel, Alex and
Knight, Kevin and
Nakamura, Satoshi and
Ney, Hermann and
Niehues, Jan and
St{\"u}ker, Sebastian and
Wu, Dekai and
Mariani, Joseph and
Yvon, Francois},
booktitle = "Proceedings of the 17th International Conference on Spoken Language Translation",
month = jul,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.iwslt-1.14",
doi = "10.18653/v1/2020.iwslt-1.14",
pages = "122--129",
abstract = "This paper describes the University of Edinburgh{'}s neural machine translation systems submitted to the IWSLT 2020 open domain Japanese$\leftrightarrow$Chinese translation task. On top of commonplace techniques like tokenisation and corpus cleaning, we explore character mapping and unsupervised decoding-time adaptation. Our techniques focus on leveraging the provided data, and we show the positive impact of each technique through the gradual improvement of BLEU.",
}
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<abstract>This paper describes the University of Edinburgh’s neural machine translation systems submitted to the IWSLT 2020 open domain JapanesełeftrightarrowChinese translation task. On top of commonplace techniques like tokenisation and corpus cleaning, we explore character mapping and unsupervised decoding-time adaptation. Our techniques focus on leveraging the provided data, and we show the positive impact of each technique through the gradual improvement of BLEU.</abstract>
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%0 Conference Proceedings
%T Character Mapping and Ad-hoc Adaptation: Edinburgh’s IWSLT 2020 Open Domain Translation System
%A Chen, Pinzhen
%A Bogoychev, Nikolay
%A Germann, Ulrich
%Y Federico, Marcello
%Y Waibel, Alex
%Y Knight, Kevin
%Y Nakamura, Satoshi
%Y Ney, Hermann
%Y Niehues, Jan
%Y Stüker, Sebastian
%Y Wu, Dekai
%Y Mariani, Joseph
%Y Yvon, Francois
%S Proceedings of the 17th International Conference on Spoken Language Translation
%D 2020
%8 July
%I Association for Computational Linguistics
%C Online
%F chen-etal-2020-character
%X This paper describes the University of Edinburgh’s neural machine translation systems submitted to the IWSLT 2020 open domain JapanesełeftrightarrowChinese translation task. On top of commonplace techniques like tokenisation and corpus cleaning, we explore character mapping and unsupervised decoding-time adaptation. Our techniques focus on leveraging the provided data, and we show the positive impact of each technique through the gradual improvement of BLEU.
%R 10.18653/v1/2020.iwslt-1.14
%U https://aclanthology.org/2020.iwslt-1.14
%U https://doi.org/10.18653/v1/2020.iwslt-1.14
%P 122-129
Markdown (Informal)
[Character Mapping and Ad-hoc Adaptation: Edinburgh’s IWSLT 2020 Open Domain Translation System](https://aclanthology.org/2020.iwslt-1.14) (Chen et al., IWSLT 2020)
ACL