Automatic Metric Validation for Grammatical Error Correction

ACL 2018

Automatic Metric Validation for Grammatical Error Correction

Jan 28, 2021
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Abstract: Metric validation in Grammatical Error Correction (GEC) is currently done by observing the correlation between hu-man and metric-induced rankings. However, such correlation studies are costly, methodologically troublesome, and suffer from low inter-rater agreement. We propose maege, an automatic methodology for GEC metric validation, that overcomes many of the difficulties in the existing methodology. Experiments with maege shed a new light on metric quality, showing for example that the standard M2 metric fares poorly on corpus-level ranking. Moreover, we use maege to perform a detailed analysis of metric behavior, showing that some types of valid edits are consistently penalized by existing metrics. Authors: Leshem Choshen, Omri Abend (The Hebrew University of Jerusalem)

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