Six Challenges for Neural Machine Translation
About
We explore six challenges for neural machine translation: domain mismatch, amount of training data, rare words, long sentences, word alignment, and beam search. We show both deficiencies and improvements over the quality of phrase-based statistical machine translation.
Philipp Koehn, Rebecca Knowles• 2017
Related benchmarks
| Task | Dataset | Result | Rank | |
|---|---|---|---|---|
| Machine Translation | IWSLT German-to-English '14 (test) | BLEU Score32.77 | 110 | |
| Visual Question Answering | VQA 2.0 (test) | Accuracy58.93 | 24 | |
| Neural Machine Translation | IWSLT and WMT (test) | PPL7.17 | 7 |
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