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doi:10.22028/D291-30983
Title: | Psycholinguistic Models of Sentence Processing Improve Sentence Readability Ranking |
Author(s): | Howcroft, David M. Demberg, Vera |
Editor(s): | Kunnemann, Florian Iñurrieta, Uxoa Camilleri, John J. Coll Ardanuy, Mariona |
Language: | English |
Title: | European Chapter of the Association for Computational Linguistics - proceedings of the Student Research Workshop : April 3-7, 2017 : EACL 2017 |
Startpage: | 958 |
Endpage: | 968 |
Publisher/Platform: | ACL |
Year of Publication: | 2017 |
Place of publication: | Stroudsburg, PA |
Title of the Conference: | EACL 2017 |
Place of the conference: | Valencia, Spain |
Publikation type: | Conference Paper |
Abstract: | While previous research on readability has typically focused on document-level measures, recent work in areas such as natural language generation has pointed out the need of sentence-level readability measures. Much of psycholinguistics has focused for many years on processing measures that provide difficulty estimates on a word-by-word basis. However, these psycholinguistic measures have not yet been tested on sentence readability ranking tasks. In this paper, we use four psycholinguistic measures: idea density, surprisal, integration cost, and embedding depth to test whether these features are predictive of readability levels. We find that psycholinguistic features significantly improve performance by up to 3 percentage points over a standard document-level readability metric baseline. |
DOI of the first publication: | 10.18653/v1/E17-1090 |
URL of the first publication: | https://www.aclweb.org/anthology/E17-1090/ |
Link to this record: | hdl:20.500.11880/29718 http://dx.doi.org/10.22028/D291-30983 |
ISBN: | 978-1-945626-37-1 |
Date of registration: | 23-Sep-2020 |
Faculty: | MI - Fakultät für Mathematik und Informatik |
Department: | MI - Informatik |
Professorship: | MI - Prof. Dr. Vera Demberg |
Collections: | SciDok - Der Wissenschaftsserver der Universität des Saarlandes |
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