English SLT and MT system description for the IWSLT 2013 evaluation

By Alexandra Birch, Matthias Huck, Nadir Durrani, Nikolay Bogoychev, Philipp Koehn. 2013

11 citations recorded by the source corpus.

Subfields: Machine Translation, Speech & Audio

How researchers see this paper

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In Machine Translation

1. Philipp Koehn
2. Nadir Durrani
3. Barry Haddow
4. Hassan Sajjad
5. Kenneth Heafield
6. Alexander M. Fraser
7. Yonatan Belinkov
8. Jesse Vig

In Speech & Audio

1. Nadir Durrani
2. Philipp Koehn
3. Kenneth Heafield

Citations in the corpus

• Edinburgh’s Phrase-based Machine Translation Systems for WMT-14 (2014, methodology): “For the English-to-German system we added an OSM model over [pos, morph] (source:pos, target:morph) and for the Germanto-English system we added an OSM model over [morph,pos] (source:morph, target:pos), a configuration that was found to work best in our previous experiments (Birch et al., 2013).”
• Integrating an Unsupervised Transliteration Model into Statistical Machine Translation (2014, methodology): “See Table 1 Baseline Settings: We trained a Moses system replicating the settings used in competition-grade systems (Durrani et al., 2013b; Birch et al., 2013): a maximum sentence length of 80, GDFA sym-metrization of GIZA++ alignments (Och and Ney, 2003), an interpolated Kneser-Ney smoothed 5-gram…”
• Investigating the Usefulness of Generalized Word Representations in SMT (2014, methodology): “, 2007), replicating the settings described in (Birch et al., 2013) developed for the 2013 Workshop on Spoken Language Translation.”