Continuous Learning from Human Post-Edits for Neural Machine Translation
Improving machine translation (MT) by learning from human post-edits is a powerful solution that is still unexplored in the neural machine translation (NMT) framework. Also in this scenario, effective techniques for the continuous tuning of an existing model to a stream of manual corrections would h...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Sciendo
2017-06-01
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| Series: | Prague Bulletin of Mathematical Linguistics |
| Online Access: | https://doi.org/10.1515/pralin-2017-0023 |