Example-based machine translation

Example-based machine translation (EBMT) approach is often characterised by its use of a bilingual corpus as its main knowledge base, at run-time. It is essentially a translation by analogy and can be viewed as an implementation of case-based reasoning approach of machine learning.

First suggested by Nagao Makoto (http://www-nagao.kuee.kyoto-u.ac.jp/member/nagao) in 1984, it soon attracted the attention of scientists in the field of natural language processing.

Example of bilingual corpus

English	Japanese
How much is that red umbrella?	Ano akai kasa wa ikura desu ka.
How much is that small camera?	Ano chiisai kamera wa ikura desu ka.

Related topics

• Machine translation
• Machine learning
• Translation memory