Abstract:
Reordering is extremely desirable for
translation accuracy when translating between high
disparity language pairs in word order. The aim of
this paper is the comparative study of lexicalized
reordering models (LRM) by Moses to investigate the
translation performance for English-Myanmar
statistical machine translation (SMT) system. The
studied methods are word-based, phrase-based and
hierarchical phrase-based LRM by using various
orientations and distortion limits. This reordering
model calculates reordering probability conditioned
on the word of each phrase pair. We applied Moses
phrase-based SMT (PBSMT) system to make
experiments for the variants of LRM and evaluated
the BLEU and RIBES scores to measure the
performance of machine translation. According to this
experiments, hierarchical phrase-based reordering
model in MSD orientation gives the highest scores in
English-Myanmar SMT system.
