InDeep × NMT: Empowering Human Translators via Interpretable Neural Machine Translation

Autor: Sarti, Gabriele, Bisazza, Arianna, Moniz, Helena, Macken, Lieve, Rufener, Andrew, Barrault, Loïc, Costa-jussà, Marta R., Declercq, Christophe, Koponen, Maarit, Kemp, Ellie, Pilos, Spyridon, Forcada, Mikel L., Scarton, Carolina, van den Bogaert, Joachim, Daems, Joke, Tezcan, Arda, Vanroy, Bram, Fonteyne, Margot

Publikováno v: Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, 313-314
STARTPAGE=313;ENDPAGE=314;TITLE=Proceedings of the 23rd Annual Conference of the European Association for Machine Translation

Neural machine translation (NMT) systems are nowadays essential components of professional translation workflows. Consequently, human translators are increasingly working as post-editors for machine-translated content. The NWO-funded InDeep project a

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::8c977e622ad21ea066790a1523f8cb22
https://research.rug.nl/en/publications/7e8a1195-9431-4560-8517-17ee3b99e808

Automatic Discrimination of Human and Neural Machine Translation: A Study with Multiple Pre-Trained Models and Longer Context

Autor: van der Werff, Tobias, van Noord, Rik, Toral, Antonio, Moniz, Helena, Macken, Lieve, Rufener, Andrew, Barrault, Loïc, Costa-jussà, Marta R., Declercq, Christophe, Koponen, Maarit, Kemp, Ellie, Pilos, Spyridon, Forcada, Mikel L., Scarton, Carolina, van den Bogaert, Joachim, Daems, Joke, Tezcan, Arda, Vanroy, Bram, Fonteyne, Margot

Publikováno v: Proceedings of the 23rd Annual Conference of the European Association for Machine Translation, 161-170
STARTPAGE=161;ENDPAGE=170;TITLE=Proceedings of the 23rd Annual Conference of the European Association for Machine Translation

We address the task of automatically distinguishing between human-translated (HT) and machine translated (MT) texts. Following recent work, we fine-tune pre-trained language models (LMs) to perform this task. Our work differs in that we use state-of-

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=narcis______::d04882ee8b906d4a9c9ecf65635fe740
https://research.rug.nl/en/publications/eaf5151f-40c5-43b7-803a-ec348921d2e9

Terminology and Translation Quality Assurance

Autor: Van den Bogaert, Joachim

Publikováno v: Recercat: Dipósit de la Recerca de Catalunya
Varias* (Consorci de Biblioteques Universitáries de Catalunya, Centre de Serveis Científics i Acadèmics de Catalunya)
Dipòsit Digital de Documents de la UAB
Universitat Autònoma de Barcelona
Tradumàtica: traducció i tecnologies de la informació i la comunicació; Núm. 6 (2008): Terminologia i traducció
Recercat. Dipósit de la Recerca de Catalunya
instname

Tot i que avui dia tothom està al cas de la gestió terminològica, encara hi ha una gran distancia entre una gestió diligent de la terminologia i la pràctica habitual. Aquest article descriu com aquestes practiques poden afectar la traducció i e

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::360f7c0fa52d523d15d2e64a5d3634a5
http://hdl.handle.net/2072/385559

Parse and Corpus-Based Machine Translation.

Autor: Vandeghinste, Vincent, Martens, Scott, Kotzé, Gideon, Tiedemann, Jörg, Van den Bogaert, Joachim, De Smet, Koen, Van Eynde, Frank, van Noord, Gertjan

Publikováno v: Essential Speech & Language Technology for Dutch; 2013, p305-319, 15p

DeBiasByUs : raising awareness and creating a database of MT bias

Autor: Daems, Joke, Hackenbuchner, Janiça

Publikováno v: Proceedings of the 23rd Annual Conference of the European Association for Machine Translation

This paper presents the project initiated by the BiasByUs team resulting from the 2021 Artificially Correct Hackaton. We briefly explain our winning participation in the hackaton, tackling the challenge on ‘Database and detection of gender bi-as in

Externí odkaz: https://explore.openaire.eu/search/publication?articleId=od_______330::061eb058b762ee0b13e131cbacf33f81
https://biblio.ugent.be/publication/8761022