Paper: Max-Margin Synchronous Grammar Induction for Machine Translation

ACL ID D13-1026
Title Max-Margin Synchronous Grammar Induction for Machine Translation
Venue Conference on Empirical Methods in Natural Language Processing
Session Main Conference
Year 2013

Traditional synchronous grammar induction estimates parameters by maximizing likeli- hood, which only has a loose relation to trans- lation quality. Alternatively, we propose a max-margin estimation approach to discrim- inatively inducing synchronous grammars for machine translation, which directly optimizes translation quality measured by BLEU. In the max-margin estimation of parameters, we only need to calculate Viterbi translations. This further facilitates the incorporation of various non-local features that are defined on the target side. We test the effectiveness of our max-margin estimation framework on a com- petitive hierarchical phrase-based system. Ex- periments show that our max-margin method significantly outperforms the traditional two- step pipeline for synchronous rule extr...