The ADAPT System Description for the STAPLE 2020 English-to-Portuguese Translation Task

Rejwanul Haque, Yasmin Moslem, Andy Way


Abstract
This paper describes the ADAPT Centre’s submission to STAPLE (Simultaneous Translation and Paraphrase for Language Education) 2020, a shared task of the 4th Workshop on Neural Generation and Translation (WNGT), for the English-to-Portuguese translation task. In this shared task, the participants were asked to produce high-coverage sets of plausible translations given English prompts (input source sentences). We present our English-to-Portuguese machine translation (MT) models that were built applying various strategies, e.g. data and sentence selection, monolingual MT for generating alternative translations, and combining multiple n-best translations. Our experiments show that adding the aforementioned techniques to the baseline yields an excellent performance in the English-to-Portuguese translation task.
Anthology ID:
2020.ngt-1.17
Volume:
Proceedings of the Fourth Workshop on Neural Generation and Translation
Month:
July
Year:
2020
Address:
Online
Venues:
ACL | NGT | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
144–152
Language:
URL:
https://aclanthology.org/2020.ngt-1.17
DOI:
10.18653/v1/2020.ngt-1.17
Bibkey:
Cite (ACL):
Rejwanul Haque, Yasmin Moslem, and Andy Way. 2020. The ADAPT System Description for the STAPLE 2020 English-to-Portuguese Translation Task. In Proceedings of the Fourth Workshop on Neural Generation and Translation, pages 144–152, Online. Association for Computational Linguistics.
Cite (Informal):
The ADAPT System Description for the STAPLE 2020 English-to-Portuguese Translation Task (Haque et al., NGT 2020)
Copy Citation:
PDF:
https://aclanthology.org/2020.ngt-1.17.pdf
Video:
 http://slideslive.com/38929831