Panning for EBMT gold, or "Remembering not to forget"
Machine Translation
Crisis MT: developing a cookbook for MT in crisis situations
WMT '11 Proceedings of the Sixth Workshop on Statistical Machine Translation
A model based transformation paradigm for cross-language collaborations
Advanced Engineering Informatics
Hi-index | 0.00 |
We describe a novel approach to MT that combines the strengths of the two leading corpus-based approaches: Phrasal SMT and EBMT. We use a syntactically informed decoder and reordering model based on the source dependency tree, in combination with conventional SMT models to incorporate the power of phrasal SMT with the linguistic generality available in a parser. We show that this approach significantly outperforms a leading string-based Phrasal SMT decoder and an EBMT system. We present results from two radically different language pairs, and investigate the sensitivity of this approach to parse quality by using two distinct parsers and oracle experiments. We also validate our automated bleu scores with a small human evaluation.