To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation
Tom Kocmi, Christian Federmann, Roman Grundkiewicz, Marcin Junczys-Dowmunt, Hitokazu Matsushita, Arul Menezes
Abstract
Automatic metrics are commonly used as the exclusive tool for declaring the superiority of one machine translation system’s quality over another. The community choice of automatic metric guides research directions and industrial developments by deciding which models are deemed better. Evaluating metrics correlations with sets of human judgements has been limited by the size of these sets. In this paper, we corroborate how reliable metrics are in contrast to human judgements on – to the best of our knowledge – the largest collection of judgements reported in the literature. Arguably, pairwise rankings of two systems are the most common evaluation tasks in research or deployment scenarios. Taking human judgement as a gold standard, we investigate which metrics have the highest accuracy in predicting translation quality rankings for such system pairs. Furthermore, we evaluate the performance of various metrics across different language pairs and domains. Lastly, we show that the sole use of BLEU impeded the development of improved models leading to bad deployment decisions. We release the collection of 2.3M sentence-level human judgements for 4380 systems for further analysis and replication of our work.- Anthology ID:
- 2021.wmt-1.57
- Volume:
- Proceedings of the Sixth Conference on Machine Translation
- Month:
- November
- Year:
- 2021
- Address:
- Online
- Venue:
- WMT
- SIG:
- SIGMT
- Publisher:
- Association for Computational Linguistics
- Note:
- Pages:
- 478–494
- Language:
- URL:
- https://aclanthology.org/2021.wmt-1.57
- DOI:
- Cite (ACL):
- Tom Kocmi, Christian Federmann, Roman Grundkiewicz, Marcin Junczys-Dowmunt, Hitokazu Matsushita, and Arul Menezes. 2021. To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation. In Proceedings of the Sixth Conference on Machine Translation, pages 478–494, Online. Association for Computational Linguistics.
- Cite (Informal):
- To Ship or Not to Ship: An Extensive Evaluation of Automatic Metrics for Machine Translation (Kocmi et al., WMT 2021)
- PDF:
- https://preview.aclanthology.org/ingestion-script-update/2021.wmt-1.57.pdf
- Code
- MicrosoftTranslator/ToShipOrNotToShip + additional community code