<?xml version="1.0" standalone="yes"?>
<Paper uid="W06-1626">
  <Title>Sydney, July 2006. c(c)2006 Association for Computational Linguistics Distributed Language Modeling for N-best List Re-ranking</Title>
  <Section position="2" start_page="0" end_page="0" type="abstr">
    <SectionTitle>
Abstract
</SectionTitle>
    <Paragraph position="0"> In this paper we describe a novel distributed language model for N-best list re-ranking. The model is based on the client/server paradigm where each server hosts a portion of the data and provides information to the client. This model allows for using an arbitrarily large corpus in a very efficient way. It also provides a natural platform for relevance weighting and selection. We applied this model on a 2.97 billion-word corpus and re-ranked the N-best list from Hiero, a state-of-the-art phrase-based system. Using BLEU as a metric, the re-ranked translation achieves a relative improvement of 4.8%, significantly better than the model-best translation. null</Paragraph>
  </Section>
class="xml-element"></Paper>