@inproceedings{bird-etal-2024-envisioning,
title = "Envisioning {NLP} for intercultural climate communication",
author = "Bird, Steven and
Aquino, Angelina and
Gumbula, Ian",
editor = "Stammbach, Dominik and
Ni, Jingwei and
Schimanski, Tobias and
Dutia, Kalyan and
Singh, Alok and
Bingler, Julia and
Christiaen, Christophe and
Kushwaha, Neetu and
Muccione, Veruska and
A. Vaghefi, Saeid and
Leippold, Markus",
booktitle = "Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024)",
month = aug,
year = "2024",
address = "Bangkok, Thailand",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/2024.climatenlp-1.8",
doi = "10.18653/v1/2024.climatenlp-1.8",
pages = "111--122",
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.",
}
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<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.</abstract>
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<date>2024-08</date>
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<start>111</start>
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%0 Conference Proceedings
%T Envisioning NLP for intercultural climate communication
%A Bird, Steven
%A Aquino, Angelina
%A Gumbula, Ian
%Y Stammbach, Dominik
%Y Ni, Jingwei
%Y Schimanski, Tobias
%Y Dutia, Kalyan
%Y Singh, Alok
%Y Bingler, Julia
%Y Christiaen, Christophe
%Y Kushwaha, Neetu
%Y Muccione, Veruska
%Y A. Vaghefi, Saeid
%Y Leippold, Markus
%S Proceedings of the 1st Workshop on Natural Language Processing Meets Climate Change (ClimateNLP 2024)
%D 2024
%8 August
%I Association for Computational Linguistics
%C Bangkok, Thailand
%F bird-etal-2024-envisioning
%X 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.
%R 10.18653/v1/2024.climatenlp-1.8
%U https://aclanthology.org/2024.climatenlp-1.8
%U https://doi.org/10.18653/v1/2024.climatenlp-1.8
%P 111-122
Markdown (Informal)
[Envisioning NLP for intercultural climate communication](https://aclanthology.org/2024.climatenlp-1.8) (Bird et al., ClimateNLP-WS 2024)
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.