Evaluating the morphological competence of Machine Translation Systems
| Autor: | François Yvon, Franck Burlot |
|---|---|
| Přispěvatelé: | dev.limsi, dev.limsi, Association for Computational Linguistics, Laboratoire d'Informatique pour la Mécanique et les Sciences de l'Ingénieur (LIMSI), Université Paris-Sud - Paris 11 (UP11)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS)-Université Paris Saclay (COmUE), Université Paris Saclay (COmUE)-Centre National de la Recherche Scientifique (CNRS)-Sorbonne Université - UFR d'Ingénierie (UFR 919), Sorbonne Université (SU)-Sorbonne Université (SU)-Université Paris-Saclay-Université Paris-Sud - Paris 11 (UP11) |
| Rok vydání: | 2017 |
| Předmět: |
Czech
evaluation Machine translation business.industry Computer science Latvian 02 engineering and technology computer.software_genre [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL] language.human_language machine translation [INFO.INFO-CL] Computer Science [cs]/Computation and Language [cs.CL] 020204 information systems morphology 0202 electrical engineering electronic engineering information engineering language 020201 artificial intelligence & image processing Artificial intelligence business computer Competence (human resources) Natural language processing |
| Zdroj: | WMT Proceedings of the Conference on Machine Translation (WMT) 2nd Conference on Machine Translation (WMT17) 2nd Conference on Machine Translation (WMT17), Association for Computational Linguistics, Sep 2017, Copenhague, Denmark. pp.43-55 |
| DOI: | 10.18653/v1/w17-4705 |
| Popis: | International audience; While recent changes in Machine Translation state-of-the-art brought translation quality a step further, it is regularly acknowledged that the standard automatic metrics do not provide enough insights to fully measure the impact of neural models. This paper proposes a new type of evaluation focused specifically on the morphological competence of a system with respect to various grammatical phenomena. Our approach uses automatically generated pairs of source sentences, where each pair tests one morphological contrast. This methodology is used to compare several systems submitted at WMT'17 for English into Czech and Latvian. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|