Pivot-based Hybrid Machine Translation to Support Multilingual Communication

Machine Translation (MT) is very useful in support- ing 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 se- mantic 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

Pivot-based hybrid machine translation to support multilingual communication for closely related languages

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 analysers, 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, such as Indonesian ethnic languages. Nevertheless, due to Indonesian ethnic languages’ characteristics, a pivot-based hybrid machine translation (PHMT) can be introduced by combining SMT and RBMT with Indonesian as a pivot, which then can be utilised in a multilingual communication support system. The PHMT translation quality was evaluated, with fluency and adequacy as metrics, and then the usability of the system was evaluated. Despite the medium average translation quality (3.05 fluency score and 3.06 adequacy score), the 3.71 average mean score of the usability evaluation indicates that the system is usable to support multilingual collaboration