Maximum entropy based phrase reordering model for statistical machine translation
Deyi Xiong, Qun Liu, Shouxun Lin · 2006
We propose a novel reordering model for phrase-based statistical machine translation (SMT) that uses a maximum entropy (MaxEnt) model to predicate reorderings of neighbor blocks (phrase pairs).The model provides content-dependent, hierarchical phrasal reordering with generalization based on features automatically learned from a real-world bitext.We present an algorithm to extract all reordering events of neighbor blocks from bilingual data.In our experiments on Chineseto-English translation, this MaxEnt-based reordering model obtains significant improvements in BLEU score on the NIST MT-05 and IWSLT-04 tasks.