The ADAPT System Description for the WMT20 News Translation Task
Venkatesh Parthasarathy, Akshai Ramesh, Rejwanul Haque, Andy Way
Abstract
This paper describes the ADAPT Centre’s submissions to the WMT20 News translation shared task for English-to-Tamil and Tamil-to-English. We present our machine translation (MT) systems that were built using the state-of-the-art neural MT (NMT) model, Transformer. We applied various strategies in order to improve our baseline MT systems, e.g. onolin- gual sentence selection for creating synthetic training data, mining monolingual sentences for adapting our MT systems to the task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Tamil and Tamil-to-English translation tasks.- Anthology ID:
- 2020.wmt-1.27
- 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:
- 262–268
- Language:
- URL:
- https://aclanthology.org/2020.wmt-1.27
- DOI:
- Bibkey:
- Cite (ACL):
- Venkatesh Parthasarathy, Akshai Ramesh, Rejwanul Haque, and Andy Way. 2020. The ADAPT System Description for the WMT20 News Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 262–268, Online. Association for Computational Linguistics.
- Cite (Informal):
- The ADAPT System Description for the WMT20 News Translation Task (Parthasarathy et al., WMT 2020)
- Copy Citation:
- PDF:
- https://aclanthology.org/2020.wmt-1.27.pdf
- Video:
- https://slideslive.com/38939616
- Data
- WikiMatrix
Export citation
@inproceedings{parthasarathy-etal-2020-adapt, title = "The {ADAPT} System Description for the {WMT}20 News Translation Task", author = "Parthasarathy, Venkatesh and Ramesh, Akshai and Haque, Rejwanul and Way, Andy", 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-1.27", pages = "262--268", abstract = "This paper describes the ADAPT Centre{'}s submissions to the WMT20 News translation shared task for English-to-Tamil and Tamil-to-English. We present our machine translation (MT) systems that were built using the state-of-the-art neural MT (NMT) model, Transformer. We applied various strategies in order to improve our baseline MT systems, e.g. onolin- gual sentence selection for creating synthetic training data, mining monolingual sentences for adapting our MT systems to the task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Tamil and Tamil-to-English translation tasks.", }
<?xml version="1.0" encoding="UTF-8"?> <modsCollection xmlns="http://www.loc.gov/mods/v3"> <mods ID="parthasarathy-etal-2020-adapt"> <titleInfo> <title>The ADAPT System Description for the WMT20 News Translation Task</title> </titleInfo> <name type="personal"> <namePart type="given">Venkatesh</namePart> <namePart type="family">Parthasarathy</namePart> <role> <roleTerm authority="marcrelator" type="text">author</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Akshai</namePart> <namePart type="family">Ramesh</namePart> <role> <roleTerm authority="marcrelator" type="text">author</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Rejwanul</namePart> <namePart type="family">Haque</namePart> <role> <roleTerm authority="marcrelator" type="text">author</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Andy</namePart> <namePart type="family">Way</namePart> <role> <roleTerm authority="marcrelator" type="text">author</roleTerm> </role> </name> <originInfo> <dateIssued>2020-11</dateIssued> </originInfo> <typeOfResource>text</typeOfResource> <relatedItem type="host"> <titleInfo> <title>Proceedings of the Fifth Conference on Machine Translation</title> </titleInfo> <name type="personal"> <namePart type="given">Loïc</namePart> <namePart type="family">Barrault</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Ondřej</namePart> <namePart type="family">Bojar</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Fethi</namePart> <namePart type="family">Bougares</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Rajen</namePart> <namePart type="family">Chatterjee</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Marta</namePart> <namePart type="given">R</namePart> <namePart type="family">Costa-jussà</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Christian</namePart> <namePart type="family">Federmann</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Mark</namePart> <namePart type="family">Fishel</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Alexander</namePart> <namePart type="family">Fraser</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Yvette</namePart> <namePart type="family">Graham</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Paco</namePart> <namePart type="family">Guzman</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Barry</namePart> <namePart type="family">Haddow</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Matthias</namePart> <namePart type="family">Huck</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Antonio</namePart> <namePart type="given">Jimeno</namePart> <namePart type="family">Yepes</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Philipp</namePart> <namePart type="family">Koehn</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">André</namePart> <namePart type="family">Martins</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Makoto</namePart> <namePart type="family">Morishita</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Christof</namePart> <namePart type="family">Monz</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Masaaki</namePart> <namePart type="family">Nagata</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Toshiaki</namePart> <namePart type="family">Nakazawa</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <name type="personal"> <namePart type="given">Matteo</namePart> <namePart type="family">Negri</namePart> <role> <roleTerm authority="marcrelator" type="text">editor</roleTerm> </role> </name> <originInfo> <publisher>Association for Computational Linguistics</publisher> <place> <placeTerm type="text">Online</placeTerm> </place> </originInfo> <genre authority="marcgt">conference publication</genre> </relatedItem> <abstract>This paper describes the ADAPT Centre’s submissions to the WMT20 News translation shared task for English-to-Tamil and Tamil-to-English. We present our machine translation (MT) systems that were built using the state-of-the-art neural MT (NMT) model, Transformer. We applied various strategies in order to improve our baseline MT systems, e.g. onolin- gual sentence selection for creating synthetic training data, mining monolingual sentences for adapting our MT systems to the task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Tamil and Tamil-to-English translation tasks.</abstract> <identifier type="citekey">parthasarathy-etal-2020-adapt</identifier> <location> <url>https://aclanthology.org/2020.wmt-1.27</url> </location> <part> <date>2020-11</date> <extent unit="page"> <start>262</start> <end>268</end> </extent> </part> </mods> </modsCollection>
%0 Conference Proceedings %T The ADAPT System Description for the WMT20 News Translation Task %A Parthasarathy, Venkatesh %A Ramesh, Akshai %A Haque, Rejwanul %A Way, Andy %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 parthasarathy-etal-2020-adapt %X This paper describes the ADAPT Centre’s submissions to the WMT20 News translation shared task for English-to-Tamil and Tamil-to-English. We present our machine translation (MT) systems that were built using the state-of-the-art neural MT (NMT) model, Transformer. We applied various strategies in order to improve our baseline MT systems, e.g. onolin- gual sentence selection for creating synthetic training data, mining monolingual sentences for adapting our MT systems to the task, hyperparameters search for Transformer in lowresource scenarios. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Tamil and Tamil-to-English translation tasks. %U https://aclanthology.org/2020.wmt-1.27 %P 262-268
Markdown (Informal)
[The ADAPT System Description for the WMT20 News Translation Task](https://aclanthology.org/2020.wmt-1.27) (Parthasarathy et al., WMT 2020)
- The ADAPT System Description for the WMT20 News Translation Task (Parthasarathy et al., WMT 2020)
ACL
- Venkatesh Parthasarathy, Akshai Ramesh, Rejwanul Haque, and Andy Way. 2020. The ADAPT System Description for the WMT20 News Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 262–268, Online. Association for Computational Linguistics.