SEDAR: a Large Scale French-English Financial Domain Parallel Corpus

TitreSEDAR: a Large Scale French-English Financial Domain Parallel Corpus
Type de publicationConference Paper
Année de publication2020
AuteursGhaddar, A., and P. Langlais
Nom de la conférenceProceedings of The 12th Language Resources and Evaluation Conference
ÉditeurEuropean Language Resources Association
Endroit d'éditionMarseille, France
ISBN Number979-10-95546-34-4
RésuméThis paper describes the acquisition, preprocessing and characteristics of SEDAR, a large scale English-French parallel corpus for the financial domain. Our extensive experiments on machine translation show that SEDAR is essential to obtain good performance on finance. We observe a large gain in the performance of machine translation systems trained on SEDAR when tested on finance, which makes SEDAR suitable to study domain adaptation for neural machine translation. The first release of the corpus comprises 8.6 million high quality sentence pairs that are publicly available for research at https://github.com/autorite/sedar-bitext.
URLhttps://www.aclweb.org/anthology/2020.lrec-1.442