On hierarchical re-ordering and permutation parsing for phrase-based decoding

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Proceedings titleProceedings of the 7th Workshop on Statistical Machine Translation (WMT 2012)
ConferenceNAACL 2012 Workshop on Statistical Machine Translation (WMT 2012), Montreal, QC, June 7-8, 2012
Pages200209; # of pages: 10
AbstractThe addition of a deterministic permutation parser can provide valuable hierarchical information to a phrase-based statistical machine translation (PBSMT) system. Permutation parsers have been used to implement hierarchical re-ordering models (Galley and Manning, 2008) and to enforce inversion transduction grammar (ITG) constraints (Feng et al., 2010). We present a number of theoretical results regarding the use of permutation parsers in PBSMT. In particular, we show that an existing ITG constraint (Zens et al., 2004) does not prevent all non-ITG permutations, and we demonstrate that the hierarchical reordering model can produce analyses during decoding that are inconsistent with analyses made during training. Experimentally, we verify the utility of hierarchical re-ordering, and compare several theoretically-motivated variants in terms of both translation quality and the syntactic complexity of their output.
Publication date
PublisherAssociation for Computational Linguistics
AffiliationInformation and Communication Technologies; National Research Council Canada
Peer reviewedYes
NPARC number20262880
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Record identifier4438fa9d-94ad-4f4b-85d7-e8dc91e0013b
Record created2012-07-10
Record modified2016-05-09
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