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<Paper uid="P05-1032">
  <Title>Scaling Phrase-Based Statistical Machine Translation to Larger Corpora and Longer Phrases</Title>
  <Section position="3" start_page="0" end_page="255" type="relat">
    <SectionTitle>
2 Related Work
</SectionTitle>
    <Paragraph position="0"> Koehn et al. (2003) compare a number of different approaches to phrase-based statistical machine  2004 large data track.</Paragraph>
    <Paragraph position="1"> translation including the joint probability phrase-based model (Marcu and Wong, 2002) and a variant on the alignment template approach (Och and Ney, 2004), and contrast them to the performance of the word-based IBM Model 4 (Brown et al., 1993). Most relevant for the work presented in this paper, they compare the effect on translation quality of using various lengths of phrases, and the size of the resulting phrase probability tables.</Paragraph>
    <Paragraph position="2"> Tillmann (2003) further examines the relationship between maximum phrase length, size of the translation table, and accuracy of translation when inducing block-based phrases from word-level alignments. Venugopal et al. (2003) and Vogel et al. (2003) present methods for achieving better translation quality by growing incrementally larger phrases by combining smaller phrases with overlapping segments. null</Paragraph>
  </Section>
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