Aye, Robot: What Happens When Robots Speak Like Real People?

In daily life, we interact with each other using the social, regional, and ethnic communication styles typical of our local communities. Successful communication further rests on our ability to seamlessly adjust to our interlocutors following the norms and expectations of our local social setting as well as conversational context and goals. However, despite significant advances in speech technology, most artificial speech systems—particularly, most social robots—still use a single, “standard”, non-local communication style for all users, social settings and interaction goals. Recent research has shown that when they interact with digital agents, humans transfer and adapt their sociolinguistic behaviours, including communication bias. Despite this, the barriers set up by this inherent communication bias have never been systematically studied for HRI; and the potential benefits to user engagement from socially inclusive, diverse communication styles have not been explored. We argue that social robotics researchers should also consider sociolinguistic factors constraining human interaction. To explore the implications, we describe two hypothetical robots designed to support the local communication style of two regions of the United Kingdom, and we consider the potential sociolinguistic impact each robot might have on its conversational partners and the wider society.

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Publication Details

Published
2025-07-05
DOI
https://doi.org/10.1145/3719160.3737615
Citations
1
Primary Topic
Social Robot Interaction and HRI
Type
article
Field-Weighted Citation Impact
2.44
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article

Aye, Robot: What Happens When Robots Speak Like Real People?

Jane Stuart‐Smith, Muneeb Ahmad, Julian Hough, Mary Ellen Foster
1 citations
Social Robot Interaction and HRI
2.44
article

Aye, Robot: What Happens When Robots Speak Like Real People?

Jane Stuart‐Smith, Muneeb Ahmad, Julian Hough, Mary Ellen Foster
article en
1 citations

Abstract

In daily life, we interact with each other using the social, regional, and ethnic communication styles typical of our local communities. Successful communication further rests on our ability to seamlessly adjust to our interlocutors following the norms and expectations of our local social setting as well as conversational context and goals. However, despite significant advances in speech technology, most artificial speech systems—particularly, most social robots—still use a single, “standard”, non-local communication style for all users, social settings and interaction goals. Recent research has shown that when they interact with digital agents, humans transfer and adapt their sociolinguistic behaviours, including communication bias. Despite this, the barriers set up by this inherent communication bias have never been systematically studied for HRI; and the potential benefits to user engagement from socially inclusive, diverse communication styles have not been explored. We argue that social robotics researchers should also consider sociolinguistic factors constraining human interaction. To explore the implications, we describe two hypothetical robots designed to support the local communication style of two regions of the United Kingdom, and we consider the potential sociolinguistic impact each robot might have on its conversational partners and the wider society.

Swansea University (GB), University of Glasgow (GB)
Openalex Percentile: Top 12%
Social Robot Interaction and HRI
2.44
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