@inproceedings{mohit-etal-2010-using,
title = "Using Variable Decoding Weight for Language Model in Statistical Machine Translation",
author = "Mohit, Behrang and
Hwa, Rebecca and
Lavie, Alon",
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.17/",
abstract = "This paper investigates varying the decoder weight of the language model (LM) when translating different parts of a sentence. We determine the condition under which the LM weight should be adapted. We find that a better translation can be achieved by varying the LM weight when decoding the most problematic spot in a sentence, which we refer to as a difficult segment. Two adaptation strategies are proposed and compared through experiments. We find that adapting a different LM weight for every difficult segment resulted in the largest improvement in translation quality."
}
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<abstract>This paper investigates varying the decoder weight of the language model (LM) when translating different parts of a sentence. We determine the condition under which the LM weight should be adapted. We find that a better translation can be achieved by varying the LM weight when decoding the most problematic spot in a sentence, which we refer to as a difficult segment. Two adaptation strategies are proposed and compared through experiments. We find that adapting a different LM weight for every difficult segment resulted in the largest improvement in translation quality.</abstract>
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%0 Conference Proceedings
%T Using Variable Decoding Weight for Language Model in Statistical Machine Translation
%A Mohit, Behrang
%A Hwa, Rebecca
%A Lavie, Alon
%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 mohit-etal-2010-using
%X This paper investigates varying the decoder weight of the language model (LM) when translating different parts of a sentence. We determine the condition under which the LM weight should be adapted. We find that a better translation can be achieved by varying the LM weight when decoding the most problematic spot in a sentence, which we refer to as a difficult segment. Two adaptation strategies are proposed and compared through experiments. We find that adapting a different LM weight for every difficult segment resulted in the largest improvement in translation quality.
%U https://aclanthology.org/2010.amta-papers.17/
Markdown (Informal)
[Using Variable Decoding Weight for Language Model in Statistical Machine Translation](https://aclanthology.org/2010.amta-papers.17/) (Mohit et al., AMTA 2010)
ACL