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Found 6 papers, 0 papers with code
DeBiasByUs: Raising Awareness and Creating a Database of MT Bias
This paper presents the project initiated by the BiasByUs team resulting from the 2021 Artificially Correct Hackaton.
Writing in a second Language with Machine translation (WiLMa)
The WiLMa project aims to assess the effects of using machine translation (MT) tools on the writing processes of second language (L2) learners of varying proficiency.
Assessing the Comprehensibility of Automatic Translations (ArisToCAT)
The ArisToCAT project aims to assess the comprehensibility of ‘raw’ (unedited) MT output for readers who can only rely on the MT output.
GECO-MT: The Ghent Eye-tracking Corpus of Machine Translation
In the present paper, we describe a large corpus of eye movement data, collected during natural reading of a human translation and a machine translation of a full novel.
On the origin of errors: A fine-grained analysis of MT and PE errors and their relationship
In order to improve the symbiosis between machine translation (MT) system and post-editor, it is not enough to know that the output of one system is better than the output of another system.
