Syntax Augmented Machine Translation via Chart Parsing
Abstract:
We present translation results on the shared task ”Exploiting Parallel Texts for Statistical Machine Translation ” generated by a chart parsing decoder operating on phrase tables augmented and generalized with target language syntactic categories. We use a target language parser to generate parse trees for each sentence on the target side of the bilingual training 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 augment (declare a syntactically motivated category for a phrase pair) and generalize (form mixed terminal and nonterminal phrases) the phrase table into a synchronous bilingual grammar. We present results on the French-to-English task for this workshop, representing significant improvements over the workshop’s baseline system. Our translation system is available open-source under the GNU General Public License. 1
Citations
| 508 | An Efficient Context-Free Parsing Algorithm – Earley - 1970 |
| 457 | The mathematics of statistical machine translation: Parameter estimation – Brown, Pietra, et al. - 1993 |
| 399 | A Maximum-Entropy-Inspired Parser – Charniak - 2000 |
| 81 | A hierarchical phrase-based model for statistical machine translation – Chiang - 2005 |
| 32 | Statistical machine translation by parsing – Melamed - 2004 |
| 23 | Better k-best parsing – Huang, Chiang - 2005 |
| 13 | phrase-based translation – Statistical |
| 3 | a beam search decoder for phrase-based statistical machine translation models. user manual – PHARAOH |
