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  license: cc
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: cc
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+ configs:
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+ - config_name: phase_1
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+ data_files: phasse_1.json
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+ - config_name: phase_2
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+ data_files: phase_.json
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+ task_categories:
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+ - translation
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+ language:
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+ - en
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+ - cs
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+ tags:
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+ - post editing
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+ size_categories:
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+ - 1K<n<10K
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  ---
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+
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+ # Neural Machine Translation Quality and Post-Editing Performance
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+
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+ This is a repository for an experiment relating NMT quality and post-editing efforts, presented at EMNLP2021 ([presentation recording](https://youtu.be/rCuoUbmJ5Uk)).
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+ Please cite the following [paper](https://aclanthology.org/2021.emnlp-main.801/) when you use this research:
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+
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+ ```
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+ @inproceedings{zouhar2021neural,
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+ title={Neural Machine Translation Quality and Post-Editing Performance},
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+ author={Zouhar, Vil{\'e}m and Popel, Martin and Bojar, Ond{\v{r}}ej and Tamchyna, Ale{\v{s}}},
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+ booktitle={Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing},
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+ pages={10204--10214},
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+ year={2021},
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+ url={https://aclanthology.org/2021.emnlp-main.801/}
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+ }
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+ ```
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+
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+ You can [access the data on huggingface](https://huggingface.co/datasets/zouharvi/nmt-pe-effects):
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+ ```python3
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+ from datasets import load_dataset
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+ data_p1 = load_dataset("zouharvi/nmt-pe-effects", "phase_1")
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+ data_p2 = load_dataset("zouharvi/nmt-pe-effects", "phase_2")
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+ ```
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+
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+ The first phase is the main one where we can see the effect of NMT quality on post-editing time.
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+ The second phase is to estimate the quality of the first post-editing round.