Toward Purely Discriminative Training for Tree-Structured Translation Models
Toward Purely Discriminative Training for Tree-Structured Translation Models
This chapter presents a method for training all the parameters of a syntax-aware statistical machine translation (MT) system in a discriminative manner. The system outperforms a generative syntax-aware baseline. Although all the standard information sources necessary for a state-of-the-art MT system have yet to be added, but the scalability of the system suggests that the main obstacle to doing so has been overcome. The next step is to generalize the tree transducer into a bitree transducer, so that it can modify the target side of the bitree after it is inferred from the source side.
Keywords: training, statistical machine translation, bitree transducer
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