COLING 2024main0 citations
A Luxembourgish Corpus as a Gender Bias Evaluation Testset
Dimitra Anastasiou, Carole Blond-Hanten, Marie Gallais
Abstract
According to the United Nations Development Programme, gender inequality is a metric that is composed of three dimensions: reproductive health, empowerment, and the labour market. Gender inequality is an obstacle to equal opportunities in society as a whole. In this paper we present our work-in-progress of designing and playing a physical game with digital elements. We currently conduct Conversation Analysis of transcribed speech of 58567 words and documenting bias. We also test OpenAI’s ChatGPT for bias in quiz-like gender-related questions.
BibTeX
@inproceedings{anastasiou-etal-2024-luxembourgish,
title = "A {L}uxembourgish Corpus as a Gender Bias Evaluation Testset",
author = "Anastasiou, Dimitra and
Blond-Hanten, Carole and
Gallais, Marie",
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.70/",
pages = "784--788"
}