Paper: Non-Isomorphic Forest Pair Translation

ACL ID D10-1043
Title Non-Isomorphic Forest Pair Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2010

This paper studies two issues, non-isomorphic structure translation and target syntactic structure usage, for statistical machine translation in the context of forest-based tree to tree sequence trans- lation. For the first issue, we propose a novel non-isomorphic translation framework to capture more non-isomorphic structure mappings than tra- ditional tree-based and tree-sequence-based trans- lation methods. For the second issue, we propose a parallel space searching method to generate hypo- thesis using tree-to-string model and evaluate its syntactic goodness using tree-to-tree/tree sequence model. This not only reduces the search complexity by merging spurious-ambiguity translation paths and solves the data sparseness issue in training, but also serves as a syntax-based tar...