Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process , tree-based translation models have shown promising progress in improving translation quality ( Liu et al. , 2006 , 2009 ; Quirk et al. , 2005 ; Galley et al. , 2004 , 2006 ; Marcu et al. , 2006 ; Shen et al. , 2008 ; Zhang et al. , 2011b ) .
treetostring alignment template for statistical machine translation
Yang Liu Qun Liu Shouxun Lin
In recent years , tree-based translation models1 are drawing more and more attention in the community of statistical machine translation ( SMT ) . Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process , tree-based translation models have shown promising progress in improving translation quality ( Liu et al. , 2006 , 2009 ; Quirk et al. , 2005 ; Galley et al. , 2004 , 2006 ; Marcu et al. , 2006 ; Shen et al. , 2008 ; Zhang et al. , 2011b ) . However , tree-based translation models always suffer from two major challenges : 1 ) They are usually built directly from parse trees , which are generated by supervised linguistic parsers .
Due to their remarkable ability to incorporate context structure information and long distance reordering into the translation process , tree-based translation models have shown promising progress in improving translation quality ( @@CITATION , 2009 ; Quirk et al. , 2005 ; Galley et al. , 2004 , 2006 ; Marcu et al. , 2006 ; Shen et al. , 2008 ; Zhang et al. , 2011b ) .