The MAKE-NMTViz Project: Meaningful, Accurate and Knowledge-limited Explanations of NMT Systems for Translators
Gabriela Gonzalez-Saez, Fabien Lopez, Mariam Nakhle, James Turner, Nicolas Ballier, Marco Dinarelli, Emmanuelle Esperança-Rodier, Sui He, Caroline Rossi, Didier Schwab, Jun Yang
Abstract
This paper describes MAKE-NMTViz, a project designed to help translators visualize neural machine translation outputs using explainable artificial intelligence visualization tools initially developed for computer vision.- Anthology ID:
- 2024.eamt-2.7
- Volume:
- Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2)
- Month:
- June
- Year:
- 2024
- Address:
- Sheffield, UK
- Editors:
- Carolina Scarton, Charlotte Prescott, Chris Bayliss, Chris Oakley, Joanna Wright, Stuart Wrigley, Xingyi Song, Edward Gow-Smith, Mikel Forcada, Helena Moniz
- Venue:
- EAMT
- SIG:
- Publisher:
- European Association for Machine Translation (EAMT)
- Note:
- Pages:
- 12–13
- Language:
- URL:
- https://aclanthology.org/2024.eamt-2.7
- DOI:
- Cite (ACL):
- Gabriela Gonzalez-Saez, Fabien Lopez, Mariam Nakhle, James Turner, Nicolas Ballier, Marco Dinarelli, Emmanuelle Esperança-Rodier, Sui He, Caroline Rossi, Didier Schwab, and Jun Yang. 2024. The MAKE-NMTViz Project: Meaningful, Accurate and Knowledge-limited Explanations of NMT Systems for Translators. In Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 2), pages 12–13, Sheffield, UK. European Association for Machine Translation (EAMT).
- Cite (Informal):
- The MAKE-NMTViz Project: Meaningful, Accurate and Knowledge-limited Explanations of NMT Systems for Translators (Gonzalez-Saez et al., EAMT 2024)
- PDF:
- https://preview.aclanthology.org/dois-2013-emnlp/2024.eamt-2.7.pdf