Dealing with Spurious Ambiguity in Learning ITG-based Word Alignment
Shujian Huang, Stephan Vogel, Jiajun Chen · 2011
Word alignment has an exponentially large search space, which often makes exact infer-ence infeasible. Recent studies have shown that inversion transduction grammars are rea-sonable constraints for word alignment, and that the constrained space could be efficiently searched using synchronous parsing algo-rithms. However, spurious ambiguity may oc-cur in synchronous parsing and cause prob-lems in both search efficiency and accuracy. In this paper, we conduct a detailed study of the causes of spurious ambiguity and how it ef-fects parsing and discriminative learning. We also propose a variant of the grammar which eliminates those ambiguities. Our grammar shows advantages over previous grammars in both synthetic and real-world experiments. 1