Abstract
Over the years a number of machine translation metrics have been developed in order to evaluate the accuracy and quality of machine-generated translations. Metrics such as BLEU and TER have been used for decades. However, with the rapid progress of machine translation systems, the need for better metrics is growing. This paper proposes an extension of the edit distance, which achieves better human correlation, whilst remaining fast, flexible and easy to understand.- Anthology ID:
- W19-5359
- Volume:
- Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1)
- Month:
- August
- Year:
- 2019
- Address:
- Florence, Italy
- Editors:
- Ondřej Bojar, Rajen Chatterjee, Christian Federmann, Mark Fishel, Yvette Graham, Barry Haddow, Matthias Huck, Antonio Jimeno Yepes, Philipp Koehn, André Martins, Christof Monz, Matteo Negri, Aurélie Névéol, Mariana Neves, Matt Post, Marco Turchi, Karin Verspoor
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 514–520
- Language:
- URL:
- https://aclanthology.org/W19-5359
- DOI:
- 10.18653/v1/W19-5359
- Cite (ACL):
- Peter Stanchev, Weiyue Wang, and Hermann Ney. 2019. EED: Extended Edit Distance Measure for Machine Translation. In Proceedings of the Fourth Conference on Machine Translation (Volume 2: Shared Task Papers, Day 1), pages 514–520, Florence, Italy. Association for Computational Linguistics.
- Cite (Informal):
- EED: Extended Edit Distance Measure for Machine Translation (Stanchev et al., WMT 2019)
- PDF:
- https://preview.aclanthology.org/ingest-acl-2023-videos/W19-5359.pdf