Syntax Augmented Machine Translation via Chart Parsing

We present translation results on the shared task ”Exploiting Parallel Texts for Statistical Machine Translation ” gener-ated by a chart parsing decoder operating on phrase tables augmented and general-ized with target language syntactic cate-gories. We use a target language parser to generate parse trees for each sentence on the target side of the bilingual train-ing corpus, matching them with phrase table lattices built for the corresponding source sentence. Considering phrases that correspond to syntactic categories in the parse trees we develop techniques to aug-ment (declare a syntactically motivated category for a phrase pair) and general-ize (form mixed terminal and nonterminal phrases) the phrase table into a synchro-nous bilingual grammar. We present re-sults on the French-to-English task for this workshop, representing significant im-provements over the workshop’s baseline system. Our translation system is avail-able open-source under the GNU General Public License.