The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task
Jindřich Libovický, Viktor Hangya, Helmut Schmid, Alexander Fraser
Abstract
We present our systems for the WMT20 Very Low Resource MT Task for translation between German and Upper Sorbian. For training our systems, we generate synthetic data by both back- and forward-translation. Additionally, we enrich the training data with German-Czech translated from Czech to Upper Sorbian by an unsupervised statistical MT system incorporating orthographically similar word pairs and transliterations of OOV words. Our best translation system between German and Sorbian is based on transfer learning from a Czech-German system and scores 12 to 13 BLEU higher than a baseline system built using the available parallel data only.- Anthology ID:
- 2020.wmt-1.131
- 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:
- 1104–1111
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.131
- DOI:
- Bibkey:
- Cite (ACL):
- Jindřich Libovický, Viktor Hangya, Helmut Schmid, and Alexander Fraser. 2020. The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task. In Proceedings of the Fifth Conference on Machine Translation, pages 1104–1111, Online. Association for Computational Linguistics.
- Cite (Informal):
- The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task (Libovický et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.131.pdf
- Video:
- https://slideslive.com/38939564
Export citation
@inproceedings{libovicky-etal-2020-lmu,
title = "The {LMU} {M}unich System for the {WMT}20 Very Low Resource Supervised {MT} Task",
author = "Libovick{\'y}, Jind{\v{r}}ich and
Hangya, Viktor and
Schmid, Helmut and
Fraser, Alexander",
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-1.131",
pages = "1104--1111",
abstract = "We present our systems for the WMT20 Very Low Resource MT Task for translation between German and Upper Sorbian. For training our systems, we generate synthetic data by both back- and forward-translation. Additionally, we enrich the training data with German-Czech translated from Czech to Upper Sorbian by an unsupervised statistical MT system incorporating orthographically similar word pairs and transliterations of OOV words. Our best translation system between German and Sorbian is based on transfer learning from a Czech-German system and scores 12 to 13 BLEU higher than a baseline system built using the available parallel data only.",
}
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%0 Conference Proceedings %T The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task %A Libovický, Jindřich %A Hangya, Viktor %A Schmid, Helmut %A Fraser, Alexander %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 libovicky-etal-2020-lmu %X We present our systems for the WMT20 Very Low Resource MT Task for translation between German and Upper Sorbian. For training our systems, we generate synthetic data by both back- and forward-translation. Additionally, we enrich the training data with German-Czech translated from Czech to Upper Sorbian by an unsupervised statistical MT system incorporating orthographically similar word pairs and transliterations of OOV words. Our best translation system between German and Sorbian is based on transfer learning from a Czech-German system and scores 12 to 13 BLEU higher than a baseline system built using the available parallel data only. %U https://aclanthology.org/2020.wmt-1.131 %P 1104-1111
Markdown (Informal)
[The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task](https://aclanthology.org/2020.wmt-1.131) (Libovický et al., WMT 2020)
- The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task (Libovický et al., WMT 2020)
ACL
- Jindřich Libovický, Viktor Hangya, Helmut Schmid, and Alexander Fraser. 2020. The LMU Munich System for the WMT20 Very Low Resource Supervised MT Task. In Proceedings of the Fifth Conference on Machine Translation, pages 1104–1111, Online. Association for Computational Linguistics.