JUST System for WMT20 Chat Translation Task

Roweida Mohammed, Mahmoud Al-Ayyoub, Malak Abdullah


Abstract
Machine Translation (MT) is a sub-field of Artificial Intelligence and Natural Language Processing that investigates and studies the ways of automatically translating a text from one language to another. In this paper, we present the details of our submission to the WMT20 Chat Translation Task, which consists of two language directions, English –> German and German –> English. The major feature of our system is applying a pre-trained BERT embedding with a bidirectional recurrent neural network. Our system ensembles three models, each with different hyperparameters. Despite being trained on a very small corpus, our model produces surprisingly good results.
Anthology ID:
2020.wmt-1.59
Volume:
Proceedings of the Fifth Conference on Machine Translation
Month:
November
Year:
2020
Address:
Online
Venue:
WMT
SIG:
SIGMT
Publisher:
Association for Computational Linguistics
Note:
Pages:
479–482
Language:
URL:
https://aclanthology.org/2020.wmt-1.59
DOI:
Bibkey:
Cite (ACL):
Roweida Mohammed, Mahmoud Al-Ayyoub, and Malak Abdullah. 2020. JUST System for WMT20 Chat Translation Task. In Proceedings of the Fifth Conference on Machine Translation, pages 479–482, Online. Association for Computational Linguistics.
Cite (Informal):
JUST System for WMT20 Chat Translation Task (Mohammed et al., WMT 2020)
Copy Citation:
PDF:
https://preview.aclanthology.org/ingestion-script-update/2020.wmt-1.59.pdf
Video:
 https://slideslive.com/38939629