What Do Dialect Speakers Want? A Survey of Attitudes Towards Language Technology for German Dialects
This addresses the needs of dialect speakers for more inclusive language technology, though it is incremental as it focuses on surveying attitudes rather than developing new tools.
The paper surveyed 327 speakers of German dialects to understand their attitudes towards NLP tools, finding strong preference for technologies that accept dialectal input, like virtual assistants, over those that produce dialectal output, such as machine translation.
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.