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Readability assessment for text simplification

Authors:

Sandra Aluisio,

Caroline Gasperin,

Carolina ScartonAuthors Info & Claims

IUNLPBEA '10: Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications

Pages 1 - 9

Published: 05 June 2010 Publication History

Abstract

We describe a readability assessment approach to support the process of text simplification for poor literacy readers. Given an input text, the goal is to predict its readability level, which corresponds to the literacy level that is expected from the target reader: rudimentary, basic or advanced. We complement features traditionally used for readability assessment with a number of new features, and experiment with alternative ways to model this problem using machine learning methods, namely classification, regression and ranking. The best resulting model is embedded in an authoring tool for Text Simplification.

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Cited By

Nassiri NCavalli-Sforza VLakhouaja A(2023)Approaches, Methods, and Resources for Assessing the Readability of Arabic TextsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/357151022:4(1-30)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3571510
Alonzo OElliot LDingman BLee SAl Amin AHuenerfauth M(2022)Reading-Assistance Tools Among Deaf and Hard-of-Hearing Computing Professionals in the U.S.: Their Reading Experiences, Interests and Perceptions of Social AccessibilityACM Transactions on Accessible Computing10.1145/352019815:2(1-31)Online publication date: 19-May-2022
https://dl.acm.org/doi/10.1145/3520198
Smadja UGrusky MArtzi YNaaman M(2019)Understanding Reader Backtracking Behavior in Online News ArticlesThe World Wide Web Conference10.1145/3308558.3313571(3237-3243)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313571
Show More Cited By

Index Terms

Readability assessment for text simplification
1. Applied computing
  1. Enterprise computing
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Language resources

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Information & Contributors

Information

Published In

cover image DL Hosted proceedings

IUNLPBEA '10: Proceedings of the NAACL HLT 2010 Fifth Workshop on Innovative Use of NLP for Building Educational Applications

June 2010

105 pages

Program Chairs:
Joel Tetreault
Educational Testing Service
,
Jill Burstein
Educational Testing Service
,
Claudia Leacock
Butler Hill Group

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 05 June 2010

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IUNLPBEA '10 Paper Acceptance Rate 13 of 28 submissions, 46%;

Overall Acceptance Rate 13 of 28 submissions, 46%

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Cited By

Nassiri NCavalli-Sforza VLakhouaja A(2023)Approaches, Methods, and Resources for Assessing the Readability of Arabic TextsACM Transactions on Asian and Low-Resource Language Information Processing10.1145/357151022:4(1-30)Online publication date: 25-Mar-2023
https://dl.acm.org/doi/10.1145/3571510
Alonzo OElliot LDingman BLee SAl Amin AHuenerfauth M(2022)Reading-Assistance Tools Among Deaf and Hard-of-Hearing Computing Professionals in the U.S.: Their Reading Experiences, Interests and Perceptions of Social AccessibilityACM Transactions on Accessible Computing10.1145/352019815:2(1-31)Online publication date: 19-May-2022
https://dl.acm.org/doi/10.1145/3520198
Smadja UGrusky MArtzi YNaaman M(2019)Understanding Reader Backtracking Behavior in Online News ArticlesThe World Wide Web Conference10.1145/3308558.3313571(3237-3243)Online publication date: 13-May-2019
https://dl.acm.org/doi/10.1145/3308558.3313571
Saggion HŠtajner SBott SMille SRello LDrndarevic B(2015)Making It SimplextACM Transactions on Accessible Computing10.1145/27380466:4(1-36)Online publication date: 11-May-2015
https://dl.acm.org/doi/10.1145/2738046
Flekova LFerschke OGurevych IChung CBroder AShim KSuel T(2014)What makes a good biography?Proceedings of the 23rd international conference on World wide web10.1145/2566486.2567972(855-866)Online publication date: 7-Apr-2014
https://dl.acm.org/doi/10.1145/2566486.2567972
Islam ZRahman MMehler A(2014)Readability Classification of Bangla TextsProceedings of the 15th International Conference on Computational Linguistics and Intelligent Text Processing - Volume 840410.1007/978-3-642-54903-8_42(507-518)Online publication date: 6-Apr-2014
https://dl.acm.org/doi/10.1007/978-3-642-54903-8_42
Barlacchi GTonelli S(2013)ERNESTAProceedings of the 14th international conference on Computational Linguistics and Intelligent Text Processing - Volume 210.1007/978-3-642-37256-8_39(476-487)Online publication date: 24-Mar-2013
https://dl.acm.org/doi/10.1007/978-3-642-37256-8_39
Ma YSingh RFosler-Lussier ELofthus R(2012)Comparing human versus automatic feature extraction for fine-grained elementary readability assessmentProceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations10.5555/2390916.2390926(58-64)Online publication date: 7-Jun-2012
https://dl.acm.org/doi/10.5555/2390916.2390926
François TMiltsakaki E(2012)Do NLP and machine learning improve traditional readability formulas?Proceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations10.5555/2390916.2390925(49-57)Online publication date: 7-Jun-2012
https://dl.acm.org/doi/10.5555/2390916.2390925
Tonelli SManh KPianta E(2012)Making readability indices readableProceedings of the First Workshop on Predicting and Improving Text Readability for target reader populations10.5555/2390916.2390924(40-48)Online publication date: 7-Jun-2012
https://dl.acm.org/doi/10.5555/2390916.2390924
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