Zobrazeno 1 - 8
of 8
pro vyhledávání: '"M. Amin Farajian"'
Publikováno v:
Prague Bulletin of Mathematical Linguistics, Vol 108, Iss 1, Pp 233-244 (2017)
Improving machine translation (MT) by learning from human post-edits is a powerful solution that is still unexplored in the neural machine translation (NMT) framework. Also in this scenario, effective techniques for the continuous tuning of an existi
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6934daa680a58f081257868897ac74a9
https://doaj.org/article/99aabafe14cc45d6864890f3c9141772
https://doaj.org/article/99aabafe14cc45d6864890f3c9141772
Publikováno v:
WMT (3)
This paper describes Unbabel's submission to the WMT2019 APE Shared Task for the English-German language pair. Following the recent rise of large, powerful, pre-trained models, we adapt the BERT pretrained model to perform Automatic Post-Editing in a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e72aae6159b55aed7f9e7b322c33652b
http://arxiv.org/abs/1905.13068
http://arxiv.org/abs/1905.13068
Publikováno v:
EACL (2)
State-of-the-art neural machine translation (NMT) systems are generally trained on specific domains by carefully selecting the training sets and applying proper domain adaptation techniques. In this paper we consider the real world scenario in which
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::92085c29a62bff33977bf2afee332b52
https://doi.org/10.18653/v1/e17-2045
https://doi.org/10.18653/v1/e17-2045
Publikováno v:
WMT
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::ad6e6e4185c85b50e433625ea9ca511b
https://doi.org/10.18653/v1/w17-4713
https://doi.org/10.18653/v1/w17-4713
Publikováno v:
HaCaT@EACL
A hot task in the Computer Assisted Translation scenario is the integration of Machine Translation (MT) systems that adapt sentence after sentence to the postedits made by the translators. A main role in the MT online adaptation process is played by
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::d802b91bd65aaba4727598be6f6d164c
https://doi.org/10.3115/v1/w14-0313
https://doi.org/10.3115/v1/w14-0313
Autor:
M. Amin Farajian, Miguel Vera, Marcos Vinícius Treviso, Jonay Trénous, André F. T. Martins, Fabio Natanael Kepler, António Góis, António V. Lopes
Publikováno v:
Scopus-Elsevier
WMT (3)
WMT (3)
We present the contribution of the Unbabel team to the WMT 2019 Shared Task on Quality Estimation. We participated on the word, sentence, and document-level tracks, encompassing 3 language pairs: English-German, English-Russian, and English-French. O
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::5e05d6b08271123a80084e35445bdb07
http://www.scopus.com/inward/record.url?eid=2-s2.0-85120999515&partnerID=MN8TOARS
http://www.scopus.com/inward/record.url?eid=2-s2.0-85120999515&partnerID=MN8TOARS
Conference
Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.
K zobrazení výsledku je třeba se přihlásit.