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The HDU Discriminative SMT System for Constrained Data PatentMT at NTCIR10
2013
NTCIR Conference on Evaluation of Information Access Technologies
We describe the statistical machine translation (SMT) systems developed at Heidelberg University for the Chinese-to-English and Japanese-to-English PatentMT subtasks at the NTCIR10 workshop. The core system used in both subtasks is a combination of hierarchical phrase-based translation and discriminative training using either large feature sets and 1/ 2 regularization (for Japanese-to-English) or variants of soft syntactic constraints (for Chinese-to-English). Our goal is to address the twofold
dblp:conf/ntcir/SimianerSJWSR13
fatcat:kw35kai7fzfjbkalrjql2gy3r4