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README.md
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---
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license: cc
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---
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---
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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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# Neural Machine Translation Quality and Post-Editing Performance
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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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@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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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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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.
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