[Corpora-List] CFP - Special issue of the ITL journal on readability and text simplification

["Thomas François"]

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First call for papers

"Current research in readability and text simplification"

A special issue of the International Journal of Applied Linguistics (ITL)
(http://poj.peeters-leuven.be/content.php?url=journal&journal_code=itl)
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With the rapid growth of the number of online documents, Internet has
become a formidable source of information. However, most of the reliable
websites are intended for rather experienced readers and can present
comprehension difficulties for certain types of readers, such as children,
learners of a foreign language, or readers with language deficits. To
offer those kind of readers a better access to information, two strategies
based on natural language processing (NLP) have been investigated in
recent years: readability and text simplification.


Readability includes a range of methods targeted at the automatic
evaluation of text difficulty in relation to a given population of
readers. Throughout the 20th century, various readability formulas have
been developped (Dale and Chall, 1948; Flesch, 1948 ; Fry, 1968). They
have been recently enhanced using various contributions from NLP, such as
language models (Collins-Thompson, 2005, Schwarm and Ostendorf, 2005 ;
Heilman et al., 2007, ...), various aspects of discourse (Pitler and
Nenkova, 2008; Feng et al., 2010) or multiword expressions (Watrin and
François, 2011). Moreover, criteria identified by researchers in
psycholinguistics or language acquisition are increasingly taken into
account.


These formulas have also been used within web plateformes, such as Read-X
(Miltsakaki, 2009) or REAP (Collins-Thompson and Callan, 2004), to help
readers find on the web documents matching their level. However, it is
sometimes the case that, for a given topic, there are no target documents
suitable for a specific user. In this context, automatic text
simplification has appeared as a possible way to make existing texts
accessible to poorer readers that would normally have trouble processing
them.


Automatic text simplification indeed aims at generating a simplified
version of an input text. Two main types of automatic simplification
methods can be distinguished : (i) lexical simplification, which aims at
replacing complex words or expressions with simpler synonyms or
paraphrases and (ii) syntactic simplification, which modifies the
structure of sentences, by deleting, moving or replacing difficult
syntactic structures. In recent years, methods for automatic
simplification have been largely influenced by other domains of NLP.
Lexical simplification, as it consists in finding a suitable synonym or
paraphrase for a complex expression, is closely related to the task of
lexical substitution, which, in turn, is related to Word Sense
Disambiguation (Specia et al., 2012). Statistical Machine Translation
methods have also influenced text simplification, as large comparable
corpora such as Wikipedia and the Simple English Wikipedia have become
available (Zhu et al., 2010 ; Wubben et al., 2012 ; ...).


This special issue will therefore address these two areas of increasing
importance, with a focus on systems informed by research on language
acquisition or used in the context of computer-assisted language learning
(CALL). To be more specific, all following contributions are suitable for
publication (the list is not exclusive):

    - readability formulas for L1 or for L2 including some NLP components
    - readability formulas taking into account some characteristics of a
specific population of learners (such as readers with a given L1,
etc.)
    - NLP approaches of text understandability.
    - lexical, syntactic, or semantic approaches of text simplification in
the context of CALL.
    - contributions of readability to text simplification
    - tools or techniques providing a more detailed difficulty diagnosis
for users (e.g. difficult words or syntactic structures).

All contributions should explicitly discuss how they relate to current
research in language acquisition, educational linguistics or
computer-assisted language learning.

MAIN DATES

- submission deadline: June 30, 2013
- first notification:  August, 31, 2013
- submission of the revised version: October 31, 2013
- final version:  December 31, 2013
- publication: 2014 (to be detailed)

Papers should be submitted in Word format through the following web site :
http://itl-sirs.sciencesconf.org/

Recommendations for authors are available at
http://itl-sirs.sciencesconf.org/resource/page/id/1

GUEST EDITORS

Thomas François (Université catholique de Louvain, Belgium)
Delphine Bernhard  (Université de Strasbourg, France)

SCIENTIFIC COMMITTEE

Kevyn Collins-Thompson (Microsoft Research)
Piet Desmet (Katholieke Universiteit Leuven)
Cédrick Fairon (Université catholique de Louvain)
Lijun Feng (Standard & Poor's)
Michael Heilman (Educational Testing Service)
Véronique Hoste (Hogeschool Gent)
Matt Huernerfauth (City University of New York)
Anne-Laure Ligozat (LIMSI-CNRS, Orsay)
Annie Louis (University of Pennsylvania
Aurélien Max (LIMSI-CNRS, Orsay)
Eleni Miltsakaki (University of Pennsylvania)
Ruslan Mitkov (University of Wolverhampton)
Marie-Francine Moens (Katholieke Universiteit Leuven)
Emily Pitler (University of Pennsylvania)
Horacio Saggion (Universitat Pompeu Fabra, Barcelona)
Advaith Siddhartan (University of Aberdeen)
Lucia Specia (University of Sheffield)
Kristian Woodsend (University of Edinburgh)
Sander Wubben (Tilburg University)


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