The transfer phase in machine translation (MT) systems has been considered to be more complicated than analysis and generation, since it is inherently a conglomeration of individual lexical rules. Currently some attempts are being made to use case-based reasoning in machine translation, that is, to make decisions on the basis of translation examples at appropriate points in MT. This paper proposes a new type of transfer system, called a Similarity-driven Transfer System (Sim Tran), for use in such case-based MT (CBMT).
['Hideo Watanabe']
A similarity-driven transfer system