Data-Driven Text Simplification

Automatic text simplification is the process of transforming a complex text into an equivalent version which would be easier to read or understand by a target audience, or easier to handle by automatic natural language processors. The transformation of the text would entail modifications at the vocabulary, syntax, and discourse levels of the text. Over the last years research in automatic text simplification has intensified not only in the number of human languages being addressed but also in the number of techniques being proposed to deal with it from initial rule-based approaches to current data-driven techniques. The aim of this tutorial is to provide a comprehensive overview of past and current research on automatic text simplification.

[1]  David Kauchak,et al.  Learning to Simplify Sentences Using Wikipedia , 2011, Monolingual@ACL.

[2]  David Kauchak,et al.  Improving Text Simplification Language Modeling Using Unsimplified Text Data , 2013, ACL.

[3]  Raman Chandrasekar,et al.  Motivations and Methods for Text Simplification , 1996, COLING.

[4]  Elena Lloret,et al.  Proyecto FIRST (Flexible Interactive Reading Support Tool): Desarrollo de una herramienta para ayudar a personas con autismo mediante la simplificación de textos , 2014, Proces. del Leng. Natural.

[5]  Wei Wu,et al.  Aligning Sentences from Standard Wikipedia to Simple Wikipedia , 2015, NAACL.

[6]  Heiner Stuckenschmidt,et al.  Sentence Alignment Methods for Improving Text Simplification Systems , 2017, ACL.

[7]  Sanja Stajner,et al.  Making It Simplext , 2015, ACM Trans. Access. Comput..

[8]  Daniel Ferrés,et al.  YATS: Yet Another Text Simplifier , 2016, NLDB.

[9]  Chris Callison-Burch,et al.  Problems in Current Text Simplification Research: New Data Can Help , 2015, TACL.

[10]  Lucia Specia,et al.  MASSAlign: Alignment and Annotation of Comparable Documents , 2017, IJCNLP.

[11]  Daniel Ferrés,et al.  Able to Read My Mail: An Accessible e-Mail Client with Assistive Technology , 2017, W4A.

[12]  Xiaojun Wan,et al.  Automatic Text Simplification , 2018, Computational Linguistics.

[13]  Advaith Siddharthan,et al.  Syntactic Simplification and Text Cohesion , 2006 .

[14]  Lucia Specia.  Translating from Complex to Simplified Sentences , 2010, PROPOR.

[15]  Mirella Lapata,et al.  Sentence Simplification with Deep Reinforcement Learning , 2017, EMNLP.

[16]  Iryna Gurevych,et al.  A Monolingual Tree-based Translation Model for Sentence Simplification , 2010, COLING.

[17]  Paolo Rosso,et al.  CATS: A Tool for Customized Alignment of Text Simplification Corpora , 2018, LREC.

[18]  Sergiu Nisioi,et al.  Exploring Neural Text Simplification Models , 2017, ACL.

[19]  Advaith Siddharthan,et al.  Hybrid text simplification using synchronous dependency grammars with hand-written and automatically harvested rules , 2014, EACL.

[20]  Chris Callison-Burch,et al.  Optimizing Statistical Machine Translation for Text Simplification , 2016, TACL.

[21]  Lucia Specia,et al.  Readability Assessment for Text Simplification , 2010 .

[22]  Sergiu Nisioi,et al.  A Detailed Evaluation of Neural Sequence-to-Sequence Models for In-domain and Cross-domain Text Simplification , 2018, LREC.

[23]  Chris Callison-Burch,et al.  Simple PPDB: A Paraphrase Database for Simplification , 2016, ACL.