THE STATISTICAL MACHINE TRANSLATION BETWEEN MYANMAR AND LISU LANGUAGES

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.