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

TL;DR

This study surveys German dialect speakers to understand their attitudes towards NLP tools, revealing preferences for input-focused technologies like virtual assistants over output-focused applications like translation.

Contribution

It provides novel insights into dialect speakers' preferences for NLP tools, highlighting the importance of input-based applications for dialectal varieties.

Findings

Strong support for dialectal input tools like virtual assistants

Less enthusiasm for dialectal output applications such as translation

Attitudes vary among different speaker subgroups

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.