Abstract:
Machine Translation is defined as the task of
transforming an existing text written in a source
language, into an equivalent text in a different
language, the target language. The statistical
machine translation approach uses two types of
information: a language model and a translation
model. In this paper, translation model is based on
the noisy channel model. We use Bayes rule to
reformulate the translation probability for
translating a foreign sentence f into English sentence
e. we use N-gram language model. In machine
translation, reordering is requiring to reorder target
phrases since different languages have different
word order requirements. In this paper, we present
Chunks-based reordering approach to reorder target
phrases. Reordering rules are automatically
generated by using bilingual corpus. The goal of this
paper is to improve the translation performance for a
Statistical Machine Translation of Myanmar to
English.
