Using Automatic Machine Translation Metrics to Analyze the Impact of Source Reformulations
Johann Roturier, Linda Mitchell, Robert Grabowski, Melanie Siegel
Abstract
This paper investigates the usefulness of automatic machine translation metrics when analyzing the impact of source reformulations on the quality of machine-translated user generated content. We propose a novel framework to quickly identify rewriting rules which improve or degrade the quality of MT output, by trying to rely on automatic metrics rather than human judgments. We find that this approach allows us to quickly identify overlapping rules between two language pairs (English- French and English-German) and specific cases where the rules’ precision could be improved.- Anthology ID:
- 2012.amta-papers.24
- Volume:
- Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers
- Month:
- October 28-November 1
- Year:
- 2012
- Address:
- San Diego, California, USA
- Venue:
- AMTA
- SIG:
- Publisher:
- Association for Machine Translation in the Americas
- Note:
- Pages:
- Language:
- URL:
- https://aclanthology.org/2012.amta-papers.24
- DOI:
- Cite (ACL):
- Johann Roturier, Linda Mitchell, Robert Grabowski, and Melanie Siegel. 2012. Using Automatic Machine Translation Metrics to Analyze the Impact of Source Reformulations. In Proceedings of the 10th Conference of the Association for Machine Translation in the Americas: Research Papers, San Diego, California, USA. Association for Machine Translation in the Americas.
- Cite (Informal):
- Using Automatic Machine Translation Metrics to Analyze the Impact of Source Reformulations (Roturier et al., AMTA 2012)
- PDF:
- https://preview.aclanthology.org/autopr/2012.amta-papers.24.pdf