Cunei is a hybrid platform for machine translation that draws upon the depth of research in Example-Based MT (EBMT) and Statistical MT (SMT). In particular, Cunei uses a data-driven approach that extends upon the basic thesis of EBMT--that some examples in the training data are of higher quality or are more relevant than others. Yet, it does so in a statistical manner, embracing much of the modeling pioneered by SMT, allowing for efficient optimization. Instead of using a static model for each phrase-pair, at run-time Cunei models each example of a phrase-pair in the corpus with respect to the input and combines them into dynamic collections of examples. Ultimately, this approach provides a more consistent model and a more flexible framework for integration of novel run-time features.
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