- Ralf D. Brown. 2001. Transfer-rule induction for example-based translation. Abstract: Previous work has shown that grammars and similar structure can be induced from unlabeled text (both monolingually and bilingually), and that the performance of an example-based machine translation (EBMT) system can be substantially enhanced by using clustering techniques to determine equivalence classes of individual words which can be used interchangeably, thus converting translation examples into templates. This paper describes the combination of these two approaches to further increase the coverage (or conversely, decrease the required training text) of an EBMT system. Preliminary results show that a reduction in required training text by a factor of twelve is possible for translation from French into English.
