| 1 |
Towards Explainable Evaluation Metrics for Natural Language Generation ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 2 |
Pushing the right buttons: adversarial evaluation of quality estimation
|
|
|
|
In: Proceedings of the Sixth Conference on Machine Translation ; 625 ; 638 (2022)
|
|
BASE
|
|
Show details
|
|
|
| 5 |
Continual Quality Estimation with Online Bayesian Meta-Learning ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 7 |
Findings of the WMT 2021 Shared Task on Quality Estimation ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 8 |
Pushing the Right Buttons: Adversarial Evaluation of Quality Estimation ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 10 |
deepQuest-py: large and distilled models for quality estimation
|
|
|
|
BASE
|
|
Show details
|
|
|
| 11 |
Findings of the WMT 2021 shared task on quality estimation
|
|
|
|
In: 689 ; 730 (2021)
|
|
BASE
|
|
Show details
|
|
|
| 12 |
deepQuest-py: large and distilled models for quality estimation
|
|
|
|
In: Proceedings of the 2021 Conference on Empirical Methods in Natural Language Processing: System Demonstrations ; 382 ; 389 (2021)
|
|
BASE
|
|
Show details
|
|
|
| 13 |
Backtranslation feedback improves user confidence in MT, not quality
|
|
Obregón, Mateo; Fomicheva, Marina; Novák, Michal; Žilinec, Matúš; Hill, Robin L; Zouhar, Vilém; Specia, Lucia; Bojar, Ondřej; Blain, Frédéric; Yankovskaya, Lisa. - : Association for Computational Linguistics, 2021
|
|
Abstract:
This is an accepted manuscript of an article published by ACL in Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics (NAACL 21). in June 2021. The accepted version of the publication may differ from the final published version. ; Translating text into a language unknown to the text’s author, dubbed outbound translation, is a modern need for which the user experience has significant room for improvement, beyond the basic machine translation facility. We demonstrate this by showing three ways in which user confidence in the outbound translation, as well as its overall final quality, can be affected: backward translation, quality estimation (with alignment) and source paraphrasing. In this paper, we describe an experiment on outbound translation from English to Czech and Estonian. We examine the effects of each proposed feedback module and further focus on how the quality of machine translation systems influence these findings and the user perception of success. We show that backward translation feedback has a mixed effect on the whole process: it increases user confidence in the produced translation, but not the objective quality.
|
|
URL: http://hdl.handle.net/2436/624021
|
|
BASE
|
|
Hide details
|
|
|
| 14 |
Knowledge distillation for quality estimation
|
|
|
|
In: 5091 ; 5099 (2021)
|
|
BASE
|
|
Show details
|
|
|
| 15 |
MLQE-PE: A Multilingual Quality Estimation and Post-Editing Dataset ...
|
|
|
|
BASE
|
|
Show details
|
|
|
| 16 |
Unsupervised quality estimation for neural machine translation
|
|
|
|
In: 8 ; 539 ; 555 (2020)
|
|
BASE
|
|
Show details
|
|
|
| 17 |
An exploratory study on multilingual quality estimation
|
|
|
|
In: 366 ; 377 (2020)
|
|
BASE
|
|
Show details
|
|
|
| 18 |
BERGAMOT-LATTE submissions for the WMT20 quality estimation shared task
|
|
|
|
In: 1010 ; 1017 (2020)
|
|
BASE
|
|
Show details
|
|
|
| 19 |
Findings of the WMT 2020 shared task on quality estimation
|
|
|
|
In: 743 ; 764 (2020)
|
|
BASE
|
|
Show details
|
|
|
| 20 |
MLQE-PE: A multilingual quality estimation and post-editing dataset
|
|
|
|
BASE
|
|
Show details
|
|
|
|
|
