NLPStatTest: A Toolkit for Comparing NLP System Performance

TL;DR

NLPStatTest is a comprehensive toolkit that automates the comparison of NLP system performance by integrating significance testing, effect size estimation, and power analysis to address both statistical and practical significance.

Contribution

The paper introduces NLPStatTest, a novel toolkit that streamlines and enhances the process of comparing NLP systems by combining multiple statistical analysis steps.

Findings

Automates significance testing, effect size estimation, and power analysis.

Provides a systematic approach for practical performance comparison.

Facilitates more meaningful NLP system evaluations.

Abstract

Statistical significance testing centered on p-values is commonly used to compare NLP system performance, but p-values alone are insufficient because statistical significance differs from practical significance. The latter can be measured by estimating effect size. In this paper, we propose a three-stage procedure for comparing NLP system performance and provide a toolkit, NLPStatTest, that automates the process. Users can upload NLP system evaluation scores and the toolkit will analyze these scores, run appropriate significance tests, estimate effect size, and conduct power analysis to estimate Type II error. The toolkit provides a convenient and systematic way to compare NLP system performance that goes beyond statistical significance testing