Automatically Learning Source-side Reordering Rules for Large Scale Machine Translation
Abstract
We describe an approach to automatically learn reordering rules to be applied as a preprocessing step in phrase-based machine
translation. We learn rules for 8 different language pairs, showing
BLEU improvements for all of them, and demonstrate that many
important order transformations (SVO to SOV or VSO, head-modifier, verb
movement) can be captured by this approach.
translation. We learn rules for 8 different language pairs, showing
BLEU improvements for all of them, and demonstrate that many
important order transformations (SVO to SOV or VSO, head-modifier, verb
movement) can be captured by this approach.
Research Areas
