We introduce EASSE, a Python package aiming to facilitate and standardise automatic evaluation and comparison of Sentence Simplification (SS) systems. EASSE provides a single access point to a broad range of evaluation resources: standard automatic metrics for assessing SS outputs (e.g. SARI), word-level accuracy scores for certain simplification transformations, reference-independent quality estimation features (e.g. compression ratio), and standard test data for SS evaluation (e.g. TurkCorpus). Finally, EASSE generates easy-to-visualise reports on the various metrics and features above and on how a particular SS output fares against reference simplifications. Through experiments, we show that these functionalities allow for better comparison and understanding of the performance of SS systems.
@article{arxiv.1908.04567,
title = {EASSE: Easier Automatic Sentence Simplification Evaluation},
author = {Fernando Alva-Manchego and Louis Martin and Carolina Scarton and Lucia Specia},
journal= {arXiv preprint arXiv:1908.04567},
year = {2019}
}