@inproceedings{borstell-2023-ableist,
title = "Ableist Language Teching over Sign Language Research",
author = {B{\"o}rstell, Carl},
editor = "Ilinykh, Nikolai and
Morger, Felix and
Dann{\'e}lls, Dana and
Dobnik, Simon and
Megyesi, Be{\'a}ta and
Nivre, Joakim",
booktitle = "Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023)",
month = may,
year = "2023",
address = "T{\'o}rshavn, the Faroe Islands",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2023.resourceful-1.1",
pages = "1--10",
abstract = "The progress made in computer-assisted linguistics has led to huge advances in natural language processing (NLP) research. This research often benefits linguistics in a broader sense, e.g., by digitizing pre-existing data and analyzing ever larger quantities of linguistic data in audio or visual form, such as sign language video data using computer vision methods. A large portion of research conducted on sign languages today is based in computer science and engineering, but much of this research is unfortunately conducted without any input from experts on the linguistics of sign languages or deaf communities. This is obvious from some of the language used in the published research, which regularly contains ableist labels. In this paper, I illustrate this by demonstrating the distribution of words in titles of research papers indexed by Google Scholar. By doing so, we see that the number of tech papers is increasing while the number of linguistics papers is (relatively) decreasing, and that ableist language is more frequent in tech papers. By extension, this suggest that much of the tech-related work on sign languages {--} heavily under-researched and under-resourced languages {--} is conducted without collaboration and consultation with deaf communities and experts, against ethical recommendations.",
}
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<abstract>The progress made in computer-assisted linguistics has led to huge advances in natural language processing (NLP) research. This research often benefits linguistics in a broader sense, e.g., by digitizing pre-existing data and analyzing ever larger quantities of linguistic data in audio or visual form, such as sign language video data using computer vision methods. A large portion of research conducted on sign languages today is based in computer science and engineering, but much of this research is unfortunately conducted without any input from experts on the linguistics of sign languages or deaf communities. This is obvious from some of the language used in the published research, which regularly contains ableist labels. In this paper, I illustrate this by demonstrating the distribution of words in titles of research papers indexed by Google Scholar. By doing so, we see that the number of tech papers is increasing while the number of linguistics papers is (relatively) decreasing, and that ableist language is more frequent in tech papers. By extension, this suggest that much of the tech-related work on sign languages – heavily under-researched and under-resourced languages – is conducted without collaboration and consultation with deaf communities and experts, against ethical recommendations.</abstract>
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%0 Conference Proceedings
%T Ableist Language Teching over Sign Language Research
%A Börstell, Carl
%Y Ilinykh, Nikolai
%Y Morger, Felix
%Y Dannélls, Dana
%Y Dobnik, Simon
%Y Megyesi, Beáta
%Y Nivre, Joakim
%S Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023)
%D 2023
%8 May
%I Association for Computational Linguistics
%C Tórshavn, the Faroe Islands
%F borstell-2023-ableist
%X The progress made in computer-assisted linguistics has led to huge advances in natural language processing (NLP) research. This research often benefits linguistics in a broader sense, e.g., by digitizing pre-existing data and analyzing ever larger quantities of linguistic data in audio or visual form, such as sign language video data using computer vision methods. A large portion of research conducted on sign languages today is based in computer science and engineering, but much of this research is unfortunately conducted without any input from experts on the linguistics of sign languages or deaf communities. This is obvious from some of the language used in the published research, which regularly contains ableist labels. In this paper, I illustrate this by demonstrating the distribution of words in titles of research papers indexed by Google Scholar. By doing so, we see that the number of tech papers is increasing while the number of linguistics papers is (relatively) decreasing, and that ableist language is more frequent in tech papers. By extension, this suggest that much of the tech-related work on sign languages – heavily under-researched and under-resourced languages – is conducted without collaboration and consultation with deaf communities and experts, against ethical recommendations.
%U https://aclanthology.org/2023.resourceful-1.1
%P 1-10
Markdown (Informal)
[Ableist Language Teching over Sign Language Research](https://aclanthology.org/2023.resourceful-1.1) (Börstell, RESOURCEFUL 2023)
ACL
- Carl Börstell. 2023. Ableist Language Teching over Sign Language Research. In Proceedings of the Second Workshop on Resources and Representations for Under-Resourced Languages and Domains (RESOURCEFUL-2023), pages 1–10, Tórshavn, the Faroe Islands. Association for Computational Linguistics.