@conference {1596,
	title = {SEDAR: a Large Scale French-English Financial Domain Parallel Corpus},
	booktitle = {Proceedings of The 12th Language Resources and Evaluation Conference},
	year = {2020},
	publisher = {European Language Resources Association},
	organization = {European Language Resources Association},
	address = {Marseille, France},
	abstract = {This 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.},
	isbn = {979-10-95546-34-4},
	url = {https://www.aclweb.org/anthology/2020.lrec-1.442},
	pdf = {http://rali.iro.umontreal.ca/rali/sites/default/files/publis/2020.lrec-1.442.pdf},
	author = {Ghaddar, Abbas and Langlais, Philippe}
}
