Pivot-Based Hybrid Machine Translation to Support Multilingual Communication

Abstract

Machine Translation (MT) is very useful in supporting multicultural communication. Existing Statistical Machine Translation (SMT) which requires high quality and quantity of corpora and Rule-Based Machine Translation (RBMT) which requires bilingual dictionaries, morphological, syntax, and semantic analyzer are scarce for low-resource languages. Due to the lack of language resources, it is difficult to create MT from high-resource languages to low-resource languages like Indonesian ethnic languages. Nevertheless, Indonesian ethnic languages' characteristics motivate us to introduce a Pivot-Based Hybrid Machine Translation (PHMT) by combining SMT and RBMT with Indonesian as a pivot which we further utilize in a multilingual communication support system. We evaluate PHMT translation quality with fluency and adequacy as metrics and then evaluate usability of the system. Despite the medium average translation quality (3.05 fluency score and 3.06 adequacy score), the 3.71 average mean scores of the usability evaluation indicates that the system is useful to support multilingual collaboration.