A Systematic Comparison between Inversion Transduction Grammar and Linear Transduction Grammar for Word Alignment

We present two contributions to grammar driven translation. First, since both Inversion Transduction Grammar and Linear Inversion Transduction Grammars have been shown to produce better alignments then the standard word alignment tool, we investigate how the trade-off between speed and end-to-end translation quality extends to the choice of grammar formalism. Second, we prove that Linear Transduction Grammars (LTGs) generate the same transductions as Linear Inversion Transduction Grammars, and present a scheme for arriving at LTGs by bilingualizing Linear Grammars. We also present a method for obtaining Inversion Transduction Grammars from Linear (Inversion) Transduction Grammars, which can speed up grammar induction from parallel corpora dramatically.