What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects

Verena Blaschke, Christoph Purschke, Hinrich Schuetze, Barbara Plank


Abstract
Natural language processing (NLP) has largely focused on modelling standardized languages. More recently, attention has increasingly shifted to local, non-standardized languages and dialects. However, the relevant speaker populations’ needs and wishes with respect to NLP tools are largely unknown. In this paper, we focus on dialects and regional languages related to German – a group of varieties that is heterogeneous in terms of prestige and standardization. We survey speakers of these varieties (N=327) and present their opinions on hypothetical language technologies for their dialects. Although attitudes vary among subgroups of our respondents, we find that respondents are especially in favour of potential NLP tools that work with dialectal input (especially audio input) such as virtual assistants, and less so for applications that produce dialectal output such as machine translation or spellcheckers.
Anthology ID:
2024.acl-short.74
Volume:
Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers)
Month:
August
Year:
2024
Address:
Bangkok, Thailand
Editors:
Lun-Wei Ku, Andre Martins, Vivek Srikumar
Venue:
ACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
823–841
Language:
URL:
https://aclanthology.org/2024.acl-short.74
DOI:
10.18653/v1/2024.acl-short.74
Bibkey:
Cite (ACL):
Verena Blaschke, Christoph Purschke, Hinrich Schuetze, and Barbara Plank. 2024. What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects. In Proceedings of the 62nd Annual Meeting of the Association for Computational Linguistics (Volume 2: Short Papers), pages 823–841, Bangkok, Thailand. Association for Computational Linguistics.
Cite (Informal):
What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects (Blaschke et al., ACL 2024)
Copy Citation:
PDF:
https://aclanthology.org/2024.acl-short.74.pdf