Reference-based Metrics can be Replaced with Reference-less Metrics in Evaluating Grammatical Error Correction Systems
In grammatical error correction (GEC), automatically evaluating system outputs requires gold-standard references, which must be created manually and thus tend to be both expensive and limited in coverage. To address this problem, a reference-less approach has recently emerged; however, previous reference-less metrics that only consider the criterion of grammaticality, have not worked as well as reference-based metrics. This study explores the potential of extending a prior grammaticality-based method to establish a reference-less evaluation method for GEC systems. Further, we empirically show that a reference-less metric that combines fluency and meaning preservation with grammaticality provides a better estimate of manual scores than that of commonly used reference-based metrics. To our knowledge, this is the first study that provides empirical evidence that a reference-less metric can replace reference-based metrics in evaluating GEC systems.
Code (0)
등록된 구현이 없습니다.
Tasks
Grammatical Error CorrectionMachine TranslationSimilar Papers 제목 키워드 기반
Is this the end of the gold standard? A straightforward reference-less grammatical error correction metric
It is difficult to rank and evaluate the performance of grammatical error correction (GEC) systems, as a sentence can be rewritten in numerous correct ways. A number of GEC metrics have been used to evaluate proposed GEC…
Grammatical Error CorrectionSentenceThere's No Comparison: Reference-less Evaluation Metrics in Grammatical Error Correction
Current methods for automatically evaluating grammatical error correction (GEC) systems rely on gold-standard references. However, these methods suffer from penalizing grammatical edits that are correct but not in the go…
BenchmarkingGrammatical Error CorrectionSentenceSOME: Reference-less Sub-Metrics Optimized for Manual Evaluations of Grammatical Error Correction
We propose a reference-less metric trained on manual evaluations of system outputs for grammatical error correction (GEC). Previous studies have shown that reference-less metrics are promising; however, existing metrics …
Grammatical Error CorrectionSentenceContext Matters for Image Descriptions for Accessibility: Challenges for Referenceless Evaluation Metrics
Few images on the Web receive alt-text descriptions that would make them accessible to blind and low vision (BLV) users. Image-based NLG systems have progressed to the point where they can begin to address this persisten…
Source-Free MT Evaluation Is Not MT Evaluation
Reference-based metrics remain the standard choice in machine translation evaluation, partly because quality estimation methods often correlate less well with human judgments. As a result, source-free, reference-based ev…
Machine Translation