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:
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PDF:
https://aclanthology.org/2012.amta-papers.24.pdf