Revisiting Optimal Decoding for Machine Translation IBM Model 4
نویسندگان
چکیده
This paper revisits optimal decoding for statistical machine translation using IBM Model 4. We show that exact/optimal inference using Integer Linear Programming is more practical than previously suggested when used in conjunction with the Cutting-Plane Algorithm. In our experiments we see that exact inference can provide a gain of up to one BLEU point for sentences of length up to 30 tokens.
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