Abstract
We explore different model architectures for the WMT 19 shared task on word-level quality estimation of automatic translation. We start with a model similar to Shef-bRNN, which we modify by using conditional random fields for sequence labelling. Additionally, we use a different approach for labelling gaps and source words. We further develop this model by including features from different sources such as BERT, baseline features for the task and transformer encoders. We evaluate the performance of our models on the English-German dataset for the corresponding shared task.- Anthology ID:
- W19-5408
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 90–94
- Language:
- URL:
- https://aclanthology.org/W19-5408
- DOI:
- 10.18653/v1/W19-5408
- Bibkey:
- Cite (ACL):
- Mikhail Mosyagin and Varvara Logacheva. 2019. MIPT System for World-Level Quality Estimation. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 90–94, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- MIPT System for World-Level Quality Estimation (Mosyagin & Logacheva, WMT 2019)
- Copy Citation:
- PDF:
- https://aclanthology.org/W19-5408.pdf
Export citation
@inproceedings{mosyagin-logacheva-2019-mipt,
title = "{MIPT} System for World-Level Quality Estimation",
author = "Mosyagin, Mikhail and
Logacheva, Varvara",
editor = "Bojar, Ond{\v{r}}ej and
Chatterjee, Rajen and
Federmann, Christian and
Fishel, Mark and
Graham, Yvette and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Monz, Christof and
Negri, Matteo and
N{\'e}v{\'e}ol, Aur{\'e}lie and
Neves, Mariana and
Post, Matt and
Turchi, Marco and
Verspoor, Karin",
booktitle = "Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2)",
month = aug,
year = "2019",
address = "Florence, Italy",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/W19-5408",
doi = "10.18653/v1/W19-5408",
pages = "90--94",
abstract = "We explore different model architectures for the WMT 19 shared task on word-level quality estimation of automatic translation. We start with a model similar to Shef-bRNN, which we modify by using conditional random fields for sequence labelling. Additionally, we use a different approach for labelling gaps and source words. We further develop this model by including features from different sources such as BERT, baseline features for the task and transformer encoders. We evaluate the performance of our models on the English-German dataset for the corresponding shared task.",
}
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%0 Conference Proceedings %T MIPT System for World-Level Quality Estimation %A Mosyagin, Mikhail %A Logacheva, Varvara %Y Bojar, Ondřej %Y Chatterjee, Rajen %Y Federmann, Christian %Y Fishel, Mark %Y Graham, Yvette %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Monz, Christof %Y Negri, Matteo %Y Névéol, Aurélie %Y Neves, Mariana %Y Post, Matt %Y Turchi, Marco %Y Verspoor, Karin %S Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2) %D 2019 %8 August %I Association for Computational Linguistics %C Florence, Italy %F mosyagin-logacheva-2019-mipt %X We explore different model architectures for the WMT 19 shared task on word-level quality estimation of automatic translation. We start with a model similar to Shef-bRNN, which we modify by using conditional random fields for sequence labelling. Additionally, we use a different approach for labelling gaps and source words. We further develop this model by including features from different sources such as BERT, baseline features for the task and transformer encoders. We evaluate the performance of our models on the English-German dataset for the corresponding shared task. %R 10.18653/v1/W19-5408 %U https://aclanthology.org/W19-5408 %U https://doi.org/10.18653/v1/W19-5408 %P 90-94
Markdown (Informal)
[MIPT System for World-Level Quality Estimation](https://aclanthology.org/W19-5408) (Mosyagin & Logacheva, WMT 2019)
- MIPT System for World-Level Quality Estimation (Mosyagin & Logacheva, WMT 2019)
ACL
- Mikhail Mosyagin and Varvara Logacheva. 2019. MIPT System for World-Level Quality Estimation. In Proceedings of the Fourth Conference on Machine Translation (Volume 3: Shared Task Papers, Day 2), pages 90–94, Florence, Italy. Association for Computational Linguistics.