The JHU Machine Translation Systems for WMT 2016

Shuoyang  Ding; Kevin  Duh; Huda  Khayrallah; Philipp Koehn; Matt Post

doi:10.18653/v1/W16-2310

The JHU Machine Translation Systems for WMT 2016

Shuoyang Ding, Kevin Duh, Huda Khayrallah, Philipp Koehn, Matt Post

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

Abstract

This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year’s evaluation campaign. Novel research directions we investigated include: neural probabilistic language models, bilingual neural network language models, morphological segmentation, and the attention based neural machine translation model as reranking feature.

Original language	English
Title of host publication	Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers
Place of Publication	Berlin, Germany
Publisher	Association for Computational Linguistics
Pages	272-280
Number of pages	9
ISBN (Electronic)	978-1-945626-10-4
DOIs	https://doi.org/10.18653/v1/W16-2310
Publication status	Published - 12 Aug 2016
Event	First Conference on Machine Translation - Berlin, Germany Duration: 11 Aug 2016 → 12 Aug 2016 http://www.statmt.org/wmt16/

Conference

Conference	First Conference on Machine Translation
Abbreviated title	WMT16
Country/Territory	Germany
City	Berlin
Period	11/08/16 → 12/08/16
Internet address	http://www.statmt.org/wmt16/

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W16-2310Final published version, 172 KBLicence: Creative Commons: Attribution (CC-BY)

https://aclanthology.coli.uni-saarland.de/papers/W16-2310/w16-2310Licence: Creative Commons: Attribution (CC-BY)

Cite this

@inproceedings{96e49a3900044d23a7e2040ca8f2c65d,

title = "The JHU Machine Translation Systems for WMT 2016",

abstract = "This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year{\textquoteright}s evaluation campaign. Novel research directions we investigated include: neural probabilistic language models, bilingual neural network language models, morphological segmentation, and the attention based neural machine translation model as reranking feature.",

author = "Shuoyang Ding and Kevin Duh and Huda Khayrallah and Philipp Koehn and Matt Post",

year = "2016",

month = aug,

day = "12",

doi = "10.18653/v1/W16-2310",

language = "English",

pages = "272--280",

booktitle = "Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers",

publisher = "Association for Computational Linguistics",

note = "First Conference on Machine Translation, WMT16 ; Conference date: 11-08-2016 Through 12-08-2016",

url = "http://www.statmt.org/wmt16/",

}

Ding, S, Duh, K, Khayrallah, H, Koehn, P & Post, M 2016, The JHU Machine Translation Systems for WMT 2016. in Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers. Association for Computational Linguistics, Berlin, Germany, pp. 272-280, First Conference on Machine Translation, Berlin, Germany, 11/08/16. https://doi.org/10.18653/v1/W16-2310

TY - GEN

T1 - The JHU Machine Translation Systems for WMT 2016

AU - Ding, Shuoyang

AU - Duh, Kevin

AU - Khayrallah, Huda

AU - Koehn, Philipp

AU - Post, Matt

PY - 2016/8/12

Y1 - 2016/8/12

N2 - This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year’s evaluation campaign. Novel research directions we investigated include: neural probabilistic language models, bilingual neural network language models, morphological segmentation, and the attention based neural machine translation model as reranking feature.

AB - This paper describes the submission of Johns Hopkins University for the shared translation task of ACL 2016 First Conference on Machine Translation (WMT 2016). We set up phrase-based, hierarchical phrase-based and syntax-based systems for all 12 language pairs of this year’s evaluation campaign. Novel research directions we investigated include: neural probabilistic language models, bilingual neural network language models, morphological segmentation, and the attention based neural machine translation model as reranking feature.

U2 - 10.18653/v1/W16-2310

DO - 10.18653/v1/W16-2310

M3 - Conference contribution

SP - 272

EP - 280

BT - Proceedings of the First Conference on Machine Translation, Volume 2: Shared Task Papers

PB - Association for Computational Linguistics

CY - Berlin, Germany

T2 - First Conference on Machine Translation

Y2 - 11 August 2016 through 12 August 2016

ER -

The JHU Machine Translation Systems for WMT 2016

Abstract

Conference

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