@inproceedings{arnardottir-etal-2022-error,
title = "Error Corpora for Different Informant Groups:Annotating and Analyzing Texts from {L}2 Speakers, People with Dyslexia and Children",
author = "Arnard{\'o}ttir, {\TH}{\'o}runn and
Glisic, Isidora and
Simonsen, Annika and
Stef{\'a}nsd{\'o}ttir, Lilja and
Ingason, Anton",
editor = "Akhtar, Md. Shad and
Chakraborty, Tanmoy",
booktitle = "Proceedings of the 19th International Conference on Natural Language Processing (ICON)",
month = dec,
year = "2022",
address = "New Delhi, India",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.icon-main.30",
pages = "245--252",
abstract = "Error corpora are useful for many tasks, in particular for developing spell and grammar checking software and teaching material and tools. We present and compare three specialized Icelandic error corpora; the Icelandic L2 Error Corpus, the Icelandic Dyslexia Error Corpus, and the Icelandic Child Language Error Corpus. Each corpus contains texts written by speakers of a particular group; L2 speakers of Icelandic, people with dyslexia, and children aged 10 to 15. The corpora shed light on errors made by these groups and their frequencies, and all errors are manually labeled according to an annotation scheme. The corpora vary in size, consisting of errors ranging from 7,817 to 24,948, and are published under a CC BY 4.0 license. In this paper, we describe the corpora and their annotation scheme, and draw comparisons between their errors and their frequencies.",
}
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<abstract>Error corpora are useful for many tasks, in particular for developing spell and grammar checking software and teaching material and tools. We present and compare three specialized Icelandic error corpora; the Icelandic L2 Error Corpus, the Icelandic Dyslexia Error Corpus, and the Icelandic Child Language Error Corpus. Each corpus contains texts written by speakers of a particular group; L2 speakers of Icelandic, people with dyslexia, and children aged 10 to 15. The corpora shed light on errors made by these groups and their frequencies, and all errors are manually labeled according to an annotation scheme. The corpora vary in size, consisting of errors ranging from 7,817 to 24,948, and are published under a CC BY 4.0 license. In this paper, we describe the corpora and their annotation scheme, and draw comparisons between their errors and their frequencies.</abstract>
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%0 Conference Proceedings
%T Error Corpora for Different Informant Groups:Annotating and Analyzing Texts from L2 Speakers, People with Dyslexia and Children
%A Arnardóttir, \THórunn
%A Glisic, Isidora
%A Simonsen, Annika
%A Stefánsdóttir, Lilja
%A Ingason, Anton
%Y Akhtar, Md. Shad
%Y Chakraborty, Tanmoy
%S Proceedings of the 19th International Conference on Natural Language Processing (ICON)
%D 2022
%8 December
%I Association for Computational Linguistics
%C New Delhi, India
%F arnardottir-etal-2022-error
%X Error corpora are useful for many tasks, in particular for developing spell and grammar checking software and teaching material and tools. We present and compare three specialized Icelandic error corpora; the Icelandic L2 Error Corpus, the Icelandic Dyslexia Error Corpus, and the Icelandic Child Language Error Corpus. Each corpus contains texts written by speakers of a particular group; L2 speakers of Icelandic, people with dyslexia, and children aged 10 to 15. The corpora shed light on errors made by these groups and their frequencies, and all errors are manually labeled according to an annotation scheme. The corpora vary in size, consisting of errors ranging from 7,817 to 24,948, and are published under a CC BY 4.0 license. In this paper, we describe the corpora and their annotation scheme, and draw comparisons between their errors and their frequencies.
%U https://aclanthology.org/2022.icon-main.30
%P 245-252
Markdown (Informal)
[Error Corpora for Different Informant Groups:Annotating and Analyzing Texts from L2 Speakers, People with Dyslexia and Children](https://aclanthology.org/2022.icon-main.30) (Arnardóttir et al., ICON 2022)
ACL