Paper: Word Alignment with Stochastic Bracketing Linear Inversion Transduction Grammar

ACL ID N10-1050
Title Word Alignment with Stochastic Bracketing Linear Inversion Transduction Grammar
Venue Human Language Technologies
Session Main Conference
Year 2010
Authors

The class of Linear Inversion Transduction Grammars (LITGs) is introduced, and used to induce a word alignment over a parallel cor- pus. We show that alignment via Stochas- tic Bracketing LITGs is considerably faster than Stochastic Bracketing ITGs, while still yielding alignments superior to the widely- used heuristic of intersecting bidirectional IBM alignments. Performance is measured as the translation quality of a phrase-based ma- chine translation system built upon the word alignments, and an improvement of 2.85 BLEU points over baseline is noted for French– English.