Thesis: Model-based Evaluation of Multilinguality

Jannis Vamvas


Abstract
The aim of this thesis was to extend the methodological toolbox for evaluating the ability of natural language processing systems to handle multiple languages. Neural machine translation (NMT) took the central role in this endeavour: NMT is inherently cross-lingual, and multilingual NMT systems, which translate from many source languages into many target languages, embody the concept of multilinguality in a very tangible way. In addition, NMT and specifically the perplexity of NMT systems can themselves be used as a tool for evaluating multilinguality.
Anthology ID:
2024.eamt-1.4
Volume:
Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1)
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, Rachel Bawden, Víctor M Sánchez-Cartagena, Patrick Cadwell, Ekaterina Lapshinova-Koltunski, Vera Cabarrão, Konstantinos Chatzitheodorou, Mary Nurminen, Diptesh Kanojia, Helena Moniz
Venue:
EAMT
SIG:
Publisher:
European Association for Machine Translation (EAMT)
Note:
Pages:
6–7
Language:
URL:
https://aclanthology.org/2024.eamt-1.4
DOI:
Bibkey:
Cite (ACL):
Jannis Vamvas. 2024. Thesis: Model-based Evaluation of Multilinguality. In Proceedings of the 25th Annual Conference of the European Association for Machine Translation (Volume 1), pages 6–7, Sheffield, UK. European Association for Machine Translation (EAMT).
Cite (Informal):
Thesis: Model-based Evaluation of Multilinguality (Vamvas, EAMT 2024)
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PDF:
https://aclanthology.org/2024.eamt-1.4.pdf