Abstract:
Natural language processing, as an essential component of artificial intelligence
technology, is rooted in a variety of disciplines, including linguistics, computer science,
and mathematics. Natural language processing's rapid advancements provide strong
support for machine translation research. The process of translating text from one language
into another using computer technology is known as Machine Translation (MT). Recently,
Statistical Machine Translation (SMT) has been proposed and it has improved in several
language pairs. The primary objective of this study is to develop a system for statistical
machine translation between Lisu and Myanmar. There are two key parts to the system
overview. Making a new parallel corpus in Lisu and Myanmar is the first stage. The second
section introduces the phrase-based statistical machine translation system for the
Myanmar-Lisu language pair. Experiments with the proposed model are carried out by
using a phrase-based statistical machine translation model. Using the BLEU score, this
system is used to evaluate the results of the translation between Myanmar and Lisu.
