Envisioning NLP for intercultural climate communication

Steven Bird, Angelina Aquino, Ian Gumbula


Abstract
Climate communication is often seen by the NLP community as an opportunity for machine translation, applied to ever smaller languages. However, over 90% the world’s linguistic diversity comes from languages with ‘primary orality’ and mostly spoken in non-Western oral societies. A case in point is the Aboriginal communities of Northern Australia, where we have been conducting workshops on climate communication, revealing shortcomings in existing communication practices along with new opportunities for improving intercultural communication. We present a case study of climate communication in an oral society, including the voices of many local people, and draw several lessons for the research program of NLP in the climate space.
Anthology ID:
2024.climatenlp-1.8
Volume:
Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Dominik Stammbach, Jingwei Ni, Tobias Schimanski, Kalyan Dutia, Alok Singh, Julia Bingler, Christophe Christiaen, Neetu Kushwaha, Veruska Muccione, Saeid A. Vaghefi, Markus Leippold
Venues:
ClimateNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
111–122
Language:
URL:
https://aclanthology.org/2024.climatenlp-1.8
DOI:
10.18653/v1/2024.climatenlp-1.8
Bibkey:
Cite (ACL):
Steven Bird, Angelina Aquino, and Ian Gumbula. 2024. Envisioning NLP for intercultural climate communication. In Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024), pages 111–122, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
Envisioning NLP for intercultural climate communication (Bird et al., ClimateNLP-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.climatenlp-1.8.pdf