BELT: Building Endangered Language Technology

Michael Ginn, David Saavedra-Beltrán, Camilo Robayo, Alexis Palmer


Abstract
The development of language technology (LT) for an endangered language is often identified as a goal in language revitalization efforts, but developing such technologies is typically subject to additional methodological challenges as well as social and ethical concerns. In particular, LT development has too often taken on colonialist qualities, extracting language data, relying on outside experts, and denying the speakers of a language sovereignty over the technologies produced.We seek to avoid such an approach through the development of the Building Endangered Language Technology (BELT) website, an educational resource designed for speakers and community members with limited technological experience to develop LTs for their own language. Specifically, BELT provides interactive lessons on basic Python programming, coupled with projects to develop specific language technologies, such as spellcheckers or word games. In this paper, we describe BELT’s design, the motivation underlying many key decisions, and preliminary responses from learners.
Anthology ID:
2024.teachingnlp-1.15
Volume:
Proceedings of the Sixth Workshop on Teaching NLP
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Sana Al-azzawi, Laura Biester, György Kovács, Ana Marasović, Leena Mathur, Margot Mieskes, Leonie Weissweiler
Venues:
TeachingNLP | WS
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
94–104
Language:
URL:
https://aclanthology.org/2024.teachingnlp-1.15
DOI:
Bibkey:
Cite (ACL):
Michael Ginn, David Saavedra-Beltrán, Camilo Robayo, and Alexis Palmer. 2024. BELT: Building Endangered Language Technology. In Proceedings of the Sixth Workshop on Teaching NLP, pages 94–104, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
BELT: Building Endangered Language Technology (Ginn et al., TeachingNLP-WS 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.teachingnlp-1.15.pdf