Rudaz2026a
| Rudaz2026a | |
|---|---|
| BibType | ARTICLE |
| Key | Rudaz2026a |
| Author(s) | Damien Rudaz, Mathias Broth, Jakub Mlynář |
| Title | Everything Counts: The Managed Omnirelevance of Speech in Human–Voice Agent Interaction |
| Editor(s) | |
| Tag(s) | EMCA, Turn-taking models, Ethnomethodology, Voice Agents, Praxeology, Conversation analysis, AI Reference List, In press |
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| Year | 2026 |
| Language | English |
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| Journal | ACM Transactions on Computer-Human Interaction |
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| URL | Link |
| DOI | 10.1145/3820655 |
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Abstract
To this day, turn-taking models determining voice agents’ conduct have been examined primarily from a technical point of view, while the ways in which they emerge as interactional constraints or resources for human conversationalists in situ remain underexplored. Drawing on a detailed analysis of corpora of naturalistic data, we document how humans’ conduct was produced in reference to the ever-present risk that, each time they spoke, their talk might trigger a new uncalled-for contribution from the artificial agent. We examine this phenomenon in interactions involving rule-based robots from a ‘pre-LLM era’ as well as the most recent voice agents. This ‘omnirelevance of human speech’ (i.e., the possibility that a conversational agent may erroneously respond to any speech it detects) emerged as a constitutive feature of these human-agent encounters. We describe some of the practices through which humans managed these artificial agents’ turn-taking conduct. Given recent improvements in voice capture technology, we ask whether this ‘omnirelevance of human speech’ weighs even more heavily on human practices today than in the past.
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