Improved chunk-level reordering for statistical machine translation
Abstract
Inspired by previous chunk-level reordering approaches to statistical machine translation,
this paper presents two methods to improve the reordering at the chunk level. By introducing
a new lattice weighting factor and by reordering the training source data, an improvement is
reported on TER and BLEU. Compared to the previous chunklevel reordering approach, the
BLEU score improves 1.4% absolutely. The translation results are reported on IWSLT
Chinese-English task.