Compact rule extraction for hierarchical phrase-based translation
Baskaran Sankaran, Gholamreza Haffari, Anoop Sarkar · 2012
This paper introduces two novel approaches for extracting compact grammars for hierarchical phrase-based translation. The first is a combinatorial optimization approach and the second is a Bayesian model over Hiero grammars using Variational Bayes for inference. In contrast to the conventional Hiero (Chiang, 2007) rule extraction algorithm, our methods extract compact models reducing model size by 17.8 % to 57.6 % without impacting translation quality across several language pairs. The Bayesian model is particularly effective for resource-poor languages with evidence from Korean-English translation. To the best of our knowledge, this is the first alternative to Hiero-style rule extraction that finds a more compact synchronous grammar without hurting translation performance. 1