@inproceedings{carter-monz-2010-discriminative,
title = "Discriminative Syntactic Reranking for Statistical Machine Translation",
author = "Carter, Simon and
Monz, Christof",
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.1",
abstract = "This paper describes a method that successfully exploits simple syntactic features for n-best translation candidate reranking using perceptrons. Our approach uses discriminative language modelling to rerank the n-best translations generated by a statistical machine translation system. The performance is evaluated for Arabic-to-English translation using NIST{'}s MT-Eval benchmarks. Whilst parse trees do not consistently help, we show how features extracted from a simple Part-of-Speech annotation layer outperform two competitive baselines, leading to significant BLEU improvements on three different test sets.",
}
Markdown (Informal)
[Discriminative Syntactic Reranking for Statistical Machine Translation](https://aclanthology.org/2010.amta-papers.1) (Carter & Monz, AMTA 2010)
ACL