Abstract
The ArisToCAT project aims to assess the comprehensibility of ‘raw’ (unedited) MT output for readers who can only rely on the MT output. In this project description, we summarize the main results of the project and present future work.- Anthology ID:
- 2020.eamt-1.64
- Volume:
- Proceedings of the 22nd Annual Conference of the European Association for Machine Translation
- Month:
- November
- Year:
- 2020
- Address:
- Lisboa, Portugal
- Editors:
- André Martins, Helena Moniz, Sara Fumega, Bruno Martins, Fernando Batista, Luisa Coheur, Carla Parra, Isabel Trancoso, Marco Turchi, Arianna Bisazza, Joss Moorkens, Ana Guerberof, Mary Nurminen, Lena Marg, Mikel L. Forcada
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation
- Note:
- Pages:
- 485–486
- Language:
- URL:
- https://aclanthology.org/2020.eamt-1.64
- DOI:
- Cite (ACL):
- Lieve Macken, Margot Fonteyne, Arda Tezcan, and Joke Daems. 2020. Assessing the Comprehensibility of Automatic Translations (ArisToCAT). In Proceedings of the 22nd Annual Conference of the European Association for Machine Translation, pages 485–486, Lisboa, Portugal. European Association for Machine Translation.
- Cite (Informal):
- Assessing the Comprehensibility of Automatic Translations (ArisToCAT) (Macken et al., EAMT 2020)
- PDF:
- https://preview.aclanthology.org/nschneid-patch-4/2020.eamt-1.64.pdf