@inproceedings{li-khudanpur-2008-large,
title = "Large-scale Discriminative n-gram Language Models for Statistical Machine Translation",
author = "Li, Zhifei and
Khudanpur, Sanjeev",
booktitle = "Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers",
month = oct # " 21-25",
year = "2008",
address = "Waikiki, USA",
publisher = "Association for Machine Translation in the Americas",
url = "https://aclanthology.org/2008.amta-papers.12",
pages = "133--142",
abstract = "We extend discriminative n-gram language modeling techniques originally proposed for automatic speech recognition to a statistical machine translation task. In this context, we propose a novel data selection method that leads to good models using a fraction of the training data. We carry out systematic experiments on several benchmark tests for Chinese to English translation using a hierarchical phrase-based machine translation system, and show that a discriminative language model significantly improves upon a state-of-the-art baseline. The experiments also highlight the benefits of our data selection method.",
}
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%0 Conference Proceedings
%T Large-scale Discriminative n-gram Language Models for Statistical Machine Translation
%A Li, Zhifei
%A Khudanpur, Sanjeev
%S Proceedings of the 8th Conference of the Association for Machine Translation in the Americas: Research Papers
%D 2008
%8 oct 21 25
%I Association for Machine Translation in the Americas
%C Waikiki, USA
%F li-khudanpur-2008-large
%X We extend discriminative n-gram language modeling techniques originally proposed for automatic speech recognition to a statistical machine translation task. In this context, we propose a novel data selection method that leads to good models using a fraction of the training data. We carry out systematic experiments on several benchmark tests for Chinese to English translation using a hierarchical phrase-based machine translation system, and show that a discriminative language model significantly improves upon a state-of-the-art baseline. The experiments also highlight the benefits of our data selection method.
%U https://aclanthology.org/2008.amta-papers.12
%P 133-142
Markdown (Informal)
[Large-scale Discriminative n-gram Language Models for Statistical Machine Translation](https://aclanthology.org/2008.amta-papers.12) (Li & Khudanpur, AMTA 2008)
ACL