Arthur Nádas
IEEE Transactions on Neural Networks
This paper proposes a new type of transfer system, called Similarity-driven Transfer System (or SimTran), which uses an example-based approach to the transfer phase of MT. In this paper, we describe a method for calculating similarity, a method for searching the most appropriate set of translation rules, and a method for constructing an output structure from those selected rules. Further, we show that SimTran can use not only translation examples but also syntax-based translation rules used in conventional transfer systems at the same time.
Arthur Nádas
IEEE Transactions on Neural Networks
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