@inproceedings{arhar-holdt-etal-2024-towards-ideal,
title = "Towards an Ideal Tool for Learner Error Annotation",
author = "Arhar Holdt, {\v{S}}pela and
Erjavec, Toma{\v{z}} and
Kosem, Iztok and
Volodina, Elena",
editor = "Calzolari, Nicoletta and
Kan, Min-Yen and
Hoste, Veronique and
Lenci, Alessandro and
Sakti, Sakriani and
Xue, Nianwen",
booktitle = "Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)",
month = may,
year = "2024",
address = "Torino, Italia",
publisher = "ELRA and ICCL",
url = "https://aclanthology.org/2024.lrec-main.1424",
pages = "16392--16398",
abstract = "Annotation and analysis of corrections in learner corpora have always presented technical challenges, mainly on account of the fact that until now there has not been any standard tool available, and that original and corrected versions of texts have been mostly stored together rather than treated as individual texts. In this paper, we present CJVT Svala 1.0, the Slovene version of the SVALA tool, which was originally used for the annotation of Swedish learner language. The localisation into Slovene resulted in the development of several new features in SVALA such as the support for multiple annotation systems, localisation into other languages, and the support for more complex annotation systems. Adopting the parallel aligned approach to text visualisation and annotation, as well as storing the data, combined with the tool supporting this, i.e. SVALA, are proposed as new standards in Learner Corpus Research.",
}
<?xml version="1.0" encoding="UTF-8"?>
<modsCollection xmlns="http://www.loc.gov/mods/v3">
<mods ID="arhar-holdt-etal-2024-towards-ideal">
<titleInfo>
<title>Towards an Ideal Tool for Learner Error Annotation</title>
</titleInfo>
<name type="personal">
<namePart type="given">Špela</namePart>
<namePart type="family">Arhar Holdt</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Tomaž</namePart>
<namePart type="family">Erjavec</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Iztok</namePart>
<namePart type="family">Kosem</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Elena</namePart>
<namePart type="family">Volodina</namePart>
<role>
<roleTerm authority="marcrelator" type="text">author</roleTerm>
</role>
</name>
<originInfo>
<dateIssued>2024-05</dateIssued>
</originInfo>
<typeOfResource>text</typeOfResource>
<relatedItem type="host">
<titleInfo>
<title>Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)</title>
</titleInfo>
<name type="personal">
<namePart type="given">Nicoletta</namePart>
<namePart type="family">Calzolari</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Min-Yen</namePart>
<namePart type="family">Kan</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Veronique</namePart>
<namePart type="family">Hoste</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Alessandro</namePart>
<namePart type="family">Lenci</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Sakriani</namePart>
<namePart type="family">Sakti</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<name type="personal">
<namePart type="given">Nianwen</namePart>
<namePart type="family">Xue</namePart>
<role>
<roleTerm authority="marcrelator" type="text">editor</roleTerm>
</role>
</name>
<originInfo>
<publisher>ELRA and ICCL</publisher>
<place>
<placeTerm type="text">Torino, Italia</placeTerm>
</place>
</originInfo>
<genre authority="marcgt">conference publication</genre>
</relatedItem>
<abstract>Annotation and analysis of corrections in learner corpora have always presented technical challenges, mainly on account of the fact that until now there has not been any standard tool available, and that original and corrected versions of texts have been mostly stored together rather than treated as individual texts. In this paper, we present CJVT Svala 1.0, the Slovene version of the SVALA tool, which was originally used for the annotation of Swedish learner language. The localisation into Slovene resulted in the development of several new features in SVALA such as the support for multiple annotation systems, localisation into other languages, and the support for more complex annotation systems. Adopting the parallel aligned approach to text visualisation and annotation, as well as storing the data, combined with the tool supporting this, i.e. SVALA, are proposed as new standards in Learner Corpus Research.</abstract>
<identifier type="citekey">arhar-holdt-etal-2024-towards-ideal</identifier>
<location>
<url>https://aclanthology.org/2024.lrec-main.1424</url>
</location>
<part>
<date>2024-05</date>
<extent unit="page">
<start>16392</start>
<end>16398</end>
</extent>
</part>
</mods>
</modsCollection>
%0 Conference Proceedings
%T Towards an Ideal Tool for Learner Error Annotation
%A Arhar Holdt, Špela
%A Erjavec, Tomaž
%A Kosem, Iztok
%A Volodina, Elena
%Y Calzolari, Nicoletta
%Y Kan, Min-Yen
%Y Hoste, Veronique
%Y Lenci, Alessandro
%Y Sakti, Sakriani
%Y Xue, Nianwen
%S Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024)
%D 2024
%8 May
%I ELRA and ICCL
%C Torino, Italia
%F arhar-holdt-etal-2024-towards-ideal
%X Annotation and analysis of corrections in learner corpora have always presented technical challenges, mainly on account of the fact that until now there has not been any standard tool available, and that original and corrected versions of texts have been mostly stored together rather than treated as individual texts. In this paper, we present CJVT Svala 1.0, the Slovene version of the SVALA tool, which was originally used for the annotation of Swedish learner language. The localisation into Slovene resulted in the development of several new features in SVALA such as the support for multiple annotation systems, localisation into other languages, and the support for more complex annotation systems. Adopting the parallel aligned approach to text visualisation and annotation, as well as storing the data, combined with the tool supporting this, i.e. SVALA, are proposed as new standards in Learner Corpus Research.
%U https://aclanthology.org/2024.lrec-main.1424
%P 16392-16398
Markdown (Informal)
[Towards an Ideal Tool for Learner Error Annotation](https://aclanthology.org/2024.lrec-main.1424) (Arhar Holdt et al., LREC-COLING 2024)
ACL
- Špela Arhar Holdt, Tomaž Erjavec, Iztok Kosem, and Elena Volodina. 2024. Towards an Ideal Tool for Learner Error Annotation. In Proceedings of the 2024 Joint International Conference on Computational Linguistics, Language Resources and Evaluation (LREC-COLING 2024), pages 16392–16398, Torino, Italia. ELRA and ICCL.