CobaltF: a fluent metric for MT evaluation

Fomicheva, Marina; Bel Rafecas, Núria; Specia, Lucia; da Cunha Fanego, Iria; Malinovskiy, Anton

CobaltF: a fluent metric for MT evaluation

License

Citation

Fomicheva M, Bel N, Specia L, da Cunha I, Malinovskiy A. CobaltF: a fluent metric for MT evaluation. In: The 54th Annual Meeting of the Association for Computational Linguistics. Proceedings of the First Conference on Machine Translation (WMT); 2016 Aug 7-12; Berlin, Germany. Stroudsburg (PA): ACL; 2016. p. 483-90.

Abstract

The vast majority of Machine Translation (MT) evaluation approaches are based on the idea that the closer the MT output is to a human reference translation, the higher its quality. While translation quality has two important aspects, adequacy and fluency, the existing referencebased metrics are largely focused on the former. In this work we combine our metric UPF-Cobalt, originally presented at the WMT15 Metrics Task, with a number of features intended to capture translation fluency. Experiments show that the integration of fluency-oriented features significantly improves the results, rivalling the best-performing evaluation metrics on the WMT15 data.

Description

Comunicació presentada a la First Conference on Machine Translation (WMT), que es va dur a terme durant el 54th Annual Meeting of the Association for Computational Linguistics, els dies 7 a 12 d'agost de 2016 a Berlín, Alemanya.