Metric Score Landscape Challenge (MSLC23): Understanding Metrics’ Performance on a Wider Landscape of Translation Quality
Chi-kiu Lo, Samuel Larkin, Rebecca E. Knowles · 2023
The Metric Score Landscape Challenge (MSLC23) dataset aims to gain insight into metric scores on a broader/wider landscape of machine translation (MT) quality.It provides a collection of low-to medium-quality MT output on the WMT23 general task test set.Together with the high quality systems submitted to the general task, this will enable better interpretation of metric scores across a range of different levels of translation quality.With this wider range of MT quality, we also visualize and analyze metric characteristics beyond just correlation.