Using Context-Dependent interpolation to Combine Statistical Language and Translation Models for Interactive Machine Translation
نویسندگان
چکیده
This work is in the context of TRANSTYPE, a system that watches over the user as he or she types a translation and repeatedly suggests completions for the text already entered. The user may either accept, modify, or ignore these suggestions. The system’s proposals are selected and scored using a linear combination of a trigram language model and a translation model. We investigate the issue of how weights should be assigned to these two models in different contexts.
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