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
- Venue:
- NGT
- 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
- 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)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2020.ngt-1.17.pdf