@inproceedings{bahar-etal-2017-rwth,
title = "The {RWTH} {A}achen Machine Translation Systems for {IWSLT} 2017",
author = "Bahar, Parnia and
Rosendahl, Jan and
Rossenbach, Nick and
Ney, Hermann",
editor = "Sakti, Sakriani and
Utiyama, Masao",
booktitle = "Proceedings of the 14th International Conference on Spoken Language Translation",
month = dec # " 14-15",
year = "2017",
address = "Tokyo, Japan",
publisher = "International Workshop on Spoken Language Translation",
url = "https://aclanthology.org/2017.iwslt-1.4/",
pages = "29--34",
abstract = "This work describes the Neural Machine Translation (NMT) system of the RWTH Aachen University developed for the English{\$}German tracks of the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2017. We use NMT systems which are augmented by state-of-the-art extensions. Furthermore, we experiment with techniques that include data filtering, a larger vocabulary, two extensions to the attention mechanism and domain adaptation. Using these methods, we can show considerable improvements over the respective baseline systems and our IWSLT 2016 submission."
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%0 Conference Proceedings
%T The RWTH Aachen Machine Translation Systems for IWSLT 2017
%A Bahar, Parnia
%A Rosendahl, Jan
%A Rossenbach, Nick
%A Ney, Hermann
%Y Sakti, Sakriani
%Y Utiyama, Masao
%S Proceedings of the 14th International Conference on Spoken Language Translation
%D 2017
%8 dec 14 15
%I International Workshop on Spoken Language Translation
%C Tokyo, Japan
%F bahar-etal-2017-rwth
%X This work describes the Neural Machine Translation (NMT) system of the RWTH Aachen University developed for the English$German tracks of the evaluation campaign of the International Workshop on Spoken Language Translation (IWSLT) 2017. We use NMT systems which are augmented by state-of-the-art extensions. Furthermore, we experiment with techniques that include data filtering, a larger vocabulary, two extensions to the attention mechanism and domain adaptation. Using these methods, we can show considerable improvements over the respective baseline systems and our IWSLT 2016 submission.
%U https://aclanthology.org/2017.iwslt-1.4/
%P 29-34
Markdown (Informal)
[The RWTH Aachen Machine Translation Systems for IWSLT 2017](https://aclanthology.org/2017.iwslt-1.4/) (Bahar et al., IWSLT 2017)
ACL
- Parnia Bahar, Jan Rosendahl, Nick Rossenbach, and Hermann Ney. 2017. The RWTH Aachen Machine Translation Systems for IWSLT 2017. In Proceedings of the 14th International Conference on Spoken Language Translation, pages 29–34, Tokyo, Japan. International Workshop on Spoken Language Translation.