@inproceedings{feng-etal-2010-source,
title = "A Source-side Decoding Sequence Model for Statistical Machine Translation",
author = "Feng, Minwei and
Mauser, Arne and
Ney, Hermann",
booktitle = "Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers",
month = oct # " 31-" # nov # " 4",
year = "2010",
address = "Denver, Colorado, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2010.amta-papers.22",
abstract = "We propose a source-side decoding sequence language model for phrase-based statistical machine translation. This model is a reordering model in the sense that it helps the decoder find the correct decoding sequence. The model uses word-aligned bilingual training data. We show improved translation quality of up to 1.34{\%} BLEU and 0.54{\%} TER using this model compared to three other widely used reordering models.",
}
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<abstract>We propose a source-side decoding sequence language model for phrase-based statistical machine translation. This model is a reordering model in the sense that it helps the decoder find the correct decoding sequence. The model uses word-aligned bilingual training data. We show improved translation quality of up to 1.34% BLEU and 0.54% TER using this model compared to three other widely used reordering models.</abstract>
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%0 Conference Proceedings
%T A Source-side Decoding Sequence Model for Statistical Machine Translation
%A Feng, Minwei
%A Mauser, Arne
%A Ney, Hermann
%S Proceedings of the 9th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2010
%8 oct 31 nov 4
%I Association for Machine Translation in the Americas
%C Denver, Colorado, USA
%F feng-etal-2010-source
%X We propose a source-side decoding sequence language model for phrase-based statistical machine translation. This model is a reordering model in the sense that it helps the decoder find the correct decoding sequence. The model uses word-aligned bilingual training data. We show improved translation quality of up to 1.34% BLEU and 0.54% TER using this model compared to three other widely used reordering models.
%U https://aclanthology.org/2010.amta-papers.22
Markdown (Informal)
[A Source-side Decoding Sequence Model for Statistical Machine Translation](https://aclanthology.org/2010.amta-papers.22) (Feng et al., AMTA 2010)
ACL