Exploring neural text simplification models

Nisioi, Sergiu ; Štajner, Sanja ; Ponzetto, Simone Paolo ; Dinu, Liviu P.

DOI: https://doi.org/10.18653/v1/P17-2014
URL: http://aclanthology.coli.uni-saarland.de/pdf/P/P17...
Additional URL: http://aclweb.org/anthology/P17-2014
Document Type: Conference or workshop publication
Year of publication: 2017
Book title: The 55th Annual Meeting of the Association for Computational Linguistics - proceedings of the conference : July 30-August 4, 2017, Vancouver, Canada : ACL 2017
Volume: 2
Page range: 85-91
Conference title: The 55th Annual Meeting of the Association for Computational Linguistics (ACL)
Location of the conference venue: Vancouver, Canada
Date of the conference: July 30 - August 4 2017
Publisher: Barzilay, Regina
Place of publication: Stroudsburg, PA
Publishing house: Association for Computational Linguistics
ISBN: 978-1-945626-76-0
Related URLs:
Publication language: English
Institution: Außerfakultäre Einrichtungen > SFB 884
School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
School of Business Informatics and Mathematics > Information Systems III: Enterprise Data Analysis (Ponzetto 2016-)
Subject: 004 Computer science, internet
Keywords (English): natural language processing , automated text simplification , neural networks
Abstract: We present the first attempt at using sequence to sequence neural networks to model text simplification (TS). Unlike the previously proposed automated TS systems, our neural text simplification (NTS) systems are able to simultaneously perform lexical simplification and content reduction. An extensive human evaluation of the output has shown that NTS systems achieve almost perfect grammaticality and meaning preservation of output sentences and higher level of simplification than the state-of-the-art automated TS systems.

Dieser Eintrag ist Teil der Universitätsbibliographie.

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