Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions
Muhammad ElNokrashy, Amr Hendy, Mohamed Abdelghaffar, Mohamed Afify, Ahmed Tawfik, Hany Hassan Awadalla
Abstract
This paper presents the description of our submission to WMT20 sentence filtering task. We combine scores from custom LASER built for each source language, a classifier built to distinguish positive and negative pairs and the original scores provided with the task. For the mBART setup, provided by the organizers, our method shows 7% and 5% relative improvement, over the baseline, in sacreBLEU score on the test set for Pashto and Khmer respectively.- Anthology ID:
- 2020.wmt-1.106
- Volume:
- Proceedings of the Fifth Conference on Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Online
- Editors:
- Loïc Barrault, Ondřej Bojar, Fethi Bougares, Rajen Chatterjee, Marta R. Costa-jussà, Christian Federmann, Mark Fishel, Alexander Fraser, Yvette Graham, Paco Guzman, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Makoto Morishita, Christof Monz, Masaaki Nagata, Toshiaki Nakazawa, Matteo Negri
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 947–951
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.106
- DOI:
- Bibkey:
- Cite (ACL):
- Muhammad ElNokrashy, Amr Hendy, Mohamed Abdelghaffar, Mohamed Afify, Ahmed Tawfik, and Hany Hassan Awadalla. 2020. Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions. In Proceedings of the Fifth Conference on Machine Translation, pages 947–951, Online. Association for Computational Linguistics.
- Cite (Informal):
- Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions (ElNokrashy et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.106.pdf
- Video:
- https://slideslive.com/38939612
Export citation
@inproceedings{elnokrashy-etal-2020-score,
title = "Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions",
author = "ElNokrashy, Muhammad and
Hendy, Amr and
Abdelghaffar, Mohamed and
Afify, Mohamed and
Tawfik, Ahmed and
Hassan Awadalla, Hany",
editor = {Barrault, Lo{\"\i}c and
Bojar, Ond{\v{r}}ej and
Bougares, Fethi and
Chatterjee, Rajen and
Costa-juss{\`a}, Marta R. and
Federmann, Christian and
Fishel, Mark and
Fraser, Alexander and
Graham, Yvette and
Guzman, Paco and
Haddow, Barry and
Huck, Matthias and
Yepes, Antonio Jimeno and
Koehn, Philipp and
Martins, Andr{\'e} and
Morishita, Makoto and
Monz, Christof and
Nagata, Masaaki and
Nakazawa, Toshiaki and
Negri, Matteo},
booktitle = "Proceedings of the Fifth Conference on Machine Translation",
month = nov,
year = "2020",
address = "Online",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2020.wmt-1.106",
pages = "947--951",
abstract = "This paper presents the description of our submission to WMT20 sentence filtering task. We combine scores from custom LASER built for each source language, a classifier built to distinguish positive and negative pairs and the original scores provided with the task. For the mBART setup, provided by the organizers, our method shows 7{\%} and 5{\%} relative improvement, over the baseline, in sacreBLEU score on the test set for Pashto and Khmer respectively.",
}
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%0 Conference Proceedings %T Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions %A ElNokrashy, Muhammad %A Hendy, Amr %A Abdelghaffar, Mohamed %A Afify, Mohamed %A Tawfik, Ahmed %A Hassan Awadalla, Hany %Y Barrault, Loïc %Y Bojar, Ondřej %Y Bougares, Fethi %Y Chatterjee, Rajen %Y Costa-jussà, Marta R. %Y Federmann, Christian %Y Fishel, Mark %Y Fraser, Alexander %Y Graham, Yvette %Y Guzman, Paco %Y Haddow, Barry %Y Huck, Matthias %Y Yepes, Antonio Jimeno %Y Koehn, Philipp %Y Martins, André %Y Morishita, Makoto %Y Monz, Christof %Y Nagata, Masaaki %Y Nakazawa, Toshiaki %Y Negri, Matteo %S Proceedings of the Fifth Conference on Machine Translation %D 2020 %8 November %I Association for Computational Linguistics %C Online %F elnokrashy-etal-2020-score %X This paper presents the description of our submission to WMT20 sentence filtering task. We combine scores from custom LASER built for each source language, a classifier built to distinguish positive and negative pairs and the original scores provided with the task. For the mBART setup, provided by the organizers, our method shows 7% and 5% relative improvement, over the baseline, in sacreBLEU score on the test set for Pashto and Khmer respectively. %U https://aclanthology.org/2020.wmt-1.106 %P 947-951
Markdown (Informal)
[Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions](https://aclanthology.org/2020.wmt-1.106) (ElNokrashy et al., WMT 2020)
- Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions (ElNokrashy et al., WMT 2020)
ACL
- Muhammad ElNokrashy, Amr Hendy, Mohamed Abdelghaffar, Mohamed Afify, Ahmed Tawfik, and Hany Hassan Awadalla. 2020. Score Combination for Improved Parallel Corpus Filtering for Low Resource Conditions. In Proceedings of the Fifth Conference on Machine Translation, pages 947–951, Online. Association for Computational Linguistics.