Discarding monotone composed rule for hierarchical phrase-based statistical machine translation

Abstract

Hierarchical phrase-based statistical machine translation systems often suffer from a huge rule table. This paper proposed a basic and efficient method for rule table reduction, discarding monotone composed rules. These rules are redundant because they may be monotonically recreated by minimal rules. Experiments show that the rule table is reduced 57%~71% without worsening translation quality.