Sentence Alignment Methods for Improving Text Simplification Systems

作者: Sanja Stajner, Marc Franco-Salvador, Simone Paolo Ponzetto, Paolo Rosso, Heiner Stuckenschmidt

摘要

We provide several methods for sentence-alignment of texts with different complexity levels. Using the best of them, we sentence-align the Newsela corpora, thus providing large training materials for automatic text simplification (ATS) systems. We show that using this dataset, even the standard phrase-based statistical machine translation models for ATS can outperform the state-of-the-art ATS systems.

PDF打开原文