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SVALA: Annotation of Second-Language Learner Text Based on Mostly Automatic Alignment of Parallel Corpora

Conference paper
Authors Mats Wirén
Arild Matsson
Dan Rosén
Elena Volodina
Published in Selected papers from the CLARIN Annual Conference 2018, Pisa, 8-10 October 2018 / edited by Inguna Skadina, Maria Eskevich
ISBN 978-91-7685-034-3
ISSN 1650-3686
Publisher Linköping University Electronic Press, Linköpings universitet
Place of publication Linköpings universitet
Publication year 2018
Published at Department of Swedish
Language en
Links www.ep.liu.se/ecp/article.asp?issue...
Keywords Normalization, Error annotation, Learner corpora, Parallel corpora, Word alignment
Subject categories General Language Studies and Linguistics, Learning, Language Technology (Computational Linguistics)

Abstract

Annotation of second-language learner text is a cumbersome manual task which in turn requires interpretation to postulate the intended meaning of the learner’s language. This paper describes SVALA, a tool which separates the logical steps in this process while providing rich visual support for each of them. The first step is to pseudonymize the learner text to fulfil the legal and ethical requirements for a distributable learner corpus. The second step is to correct the text, which is carried out in the simplest possible way by text editing. During the editing, SVALA automatically maintains a parallel corpus with alignments between words in the learner source text and corrected text, while the annotator may repair inconsistent word alignments. Finally, the actual labelling of the corrections (the postulated errors) is performed. We describe the objectives, design and workflow of SVALA, and our plans for further development.

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