Conventional approaches to machine translation require many linguistic resources either as transfer rules or parallel corpora. However, we are attempting to measure how little knowledge can be used for machine translation between similar languages, starting off with only a transfer dictionary and a target language corpus. The proposed method of machine translation exploits the linguistic similarities to achieve acceptable translation with low cost. We introduce Japanese to Korean machine translation as a case study.
Japaese, Korean, machine translation, monolingual corpus, transfer lexicon