Of Human Criteria and Automatic Metrics: A Benchmark of the Evaluation of Story Generation

Cyril Chhun, Pierre Colombo, C. Clavel, Fabian M. Suchanek
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引用次数: 18

Abstract

Research on Automatic Story Generation (ASG) relies heavily on human and automatic evaluation. However, there is no consensus on which human evaluation criteria to use, and no analysis of how well automatic criteria correlate with them. In this paper, we propose to re-evaluate ASG evaluation. We introduce a set of 6 orthogonal and comprehensive human criteria, carefully motivated by the social sciences literature. We also present HANNA, an annotated dataset of 1,056 stories produced by 10 different ASG systems. HANNA allows us to quantitatively evaluate the correlations of 72 automatic metrics with human criteria. Our analysis highlights the weaknesses of current metrics for ASG and allows us to formulate practical recommendations for ASG evaluation.
人的标准与自动度量:故事生成评价的基准
自动故事生成(ASG)的研究很大程度上依赖于人工和自动评估。然而,对于使用哪种人类评估标准没有达成共识,也没有分析自动标准与它们之间的关系有多好。在本文中,我们建议重新评估ASG的评价。我们引入了一套6个正交和全面的人类标准,精心激发了社会科学文献。我们还介绍了HANNA,这是一个由10个不同的ASG系统生成的1,056个故事的注释数据集。HANNA允许我们定量地评估72个自动指标与人类标准的相关性。我们的分析突出了当前ASG指标的弱点,并使我们能够为ASG评估制定实用的建议。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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