Learning to Translate with Source and Target Syntax
David Chiang · 2010
Statistical translation models that try to capture the recursive structure of language have been widely adopted over the last few years. These models make use of vary-ing amounts of information from linguis-tic theory: some use none at all, some use information about the grammar of the tar-get language, some use information about the grammar of the source language. But progress has been slower on translation models that are able to learn the rela-tionship between the grammars of both the source and target language. We dis-cuss the reasons why this has been a chal-lenge, review existing attempts to meet this challenge, and show how some old and new ideas can be combined into a sim-ple approach that uses both source and tar-get syntax for significant improvements in translation accuracy. 1