Building The First English-Brazilian Portuguese Corpus for Automatic Post-Editing
Felipe Almeida Costa, Thiago Castro Ferreira, Adriana Pagano, Wagner Meira
Abstract
This paper introduces the first corpus for Automatic Post-Editing of English and a low-resource language, Brazilian Portuguese. The source English texts were extracted from the WebNLG corpus and automatically translated into Portuguese using a state-of-the-art industrial neural machine translator. Post-edits were then obtained in an experiment with native speakers of Brazilian Portuguese. To assess the quality of the corpus, we performed error analysis and computed complexity indicators measuring how difficult the APE task would be. We report preliminary results of Phrase-Based and Neural Machine Translation Models on this new corpus. Data and code publicly available in our repository.
BibTeX
@inproceedings{almeida-costa-etal-2020-building,
title = "Building The First {E}nglish-{B}razilian {P}ortuguese Corpus for Automatic Post-Editing",
author = "Almeida Costa, Felipe and
Castro Ferreira, Thiago and
Pagano, Adriana and
Meira, Wagner",
editor = "Scott, Donia and
Bel, Nuria and
Zong, Chengqing",
booktitle = "Proceedings of the 28th International Conference on Computational Linguistics",
month = dec,
year = "2020",
address = "Barcelona, Spain (Online)",
publisher = "International Committee on Computational Linguistics",
url = "https://aclanthology.org/2020.coling-main.533/",
doi = "10.18653/v1/2020.coling-main.533",
pages = "6063--6069"
}