Challenges and Strategies in Cross-Cultural NLP
Daniel Hershcovich, Stella Frank, Heather Lent, Miryam de Lhoneux, Mostafa Abdou, Stephanie Brandl, Emanuele Bugliarello, Laura Cabello Piqueras
Abstract
Various efforts in the Natural Language Processing (NLP) community have been made to accommodate linguistic diversity and serve speakers of many different languages. However, it is important to acknowledge that speakers and the content they produce and require, vary not just by language, but also by culture. Although language and culture are tightly linked, there are important differences. Analogous to cross-lingual and multilingual NLP, cross-cultural and multicultural NLP considers these differences in order to better serve users of NLP systems. We propose a principled framework to frame these efforts, and survey existing and potential strategies.
BibTeX
@inproceedings{hershcovich-etal-2022-challenges,
title = "Challenges and Strategies in Cross-Cultural {NLP}",
author = "Hershcovich, Daniel and
Frank, Stella and
Lent, Heather and
de Lhoneux, Miryam and
Abdou, Mostafa and
Brandl, Stephanie and
Bugliarello, Emanuele and
Cabello Piqueras, Laura and
Chalkidis, Ilias and
Cui, Ruixiang and
Fierro, Constanza and
Margatina, Katerina and
Rust, Phillip and
S{\o}gaard, Anders",
editor = "Muresan, Smaranda and
Nakov, Preslav and
Villavicencio, Aline",
booktitle = "Proceedings of the 60th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers)",
month = may,
year = "2022",
address = "Dublin, Ireland",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2022.acl-long.482/",
doi = "10.18653/v1/2022.acl-long.482",
pages = "6997--7013"
}