近縁言語のための帰納的な対訳辞書生成フレームワーク

京都大学0048新制・課程博士博士(情報学)甲第21395号情博第681号新制||情||117(附属図書館)京都大学大学院情報学研究科社会情報学専攻(主査)教授 石田 亨, 教授 吉川 正俊, 教授 河原 達也学位規則第4条第1項該当Doctor of InformaticsKyoto UniversityDFA

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