Mapping Perceptions of Humanness in Speech-Based Intelligent Personal Assistant Interaction
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Abstract (arXiv)
Humanness is core to speech interface design. Yet little is known about how users conceptualise perceptions of humanness and how people define their interaction with speech interfaces through this. To map these perceptions n=21 participants held dialogues with a human and two speech interface based intelligent personal assistants, and then reflected and compared their experiences using the repertory grid technique. Analysis of the constructs show that perceptions of humanness are multidimensional, focusing on eight key themes: partner knowledge set, interpersonal connection, linguistic content, partner performance and capabilities, conversational interaction, partner identity and role, vocal qualities and behavioral affordances. Through these themes, it is clear that users define the capabilities of speech interfaces differently to humans, seeing them as more formal, fact based, impersonal and less authentic. Based on the findings, we discuss how the themes help to scaffold, categorise and target research and design efforts, considering the appropriateness of emulating humanness.
Key facts. Cited by 10 papers in the map (data through 14 Oct 2026). First posted on arXiv 26 Jul 2019.
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Citing papers per year: 2021: 2; 2022: 0; 2023: 1; 2024: 4; 2025: 1; 2026: 2.
10 papers.
- 2023Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perceptioncited by 19
- 2024Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysiscited by 7
- 2024Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Designcited by 5
- 2025Toward Metaphor-Fluid Conversation Design for Voice User Interfacescited by 5
- 2021What Do We See in Them? Identifying Dimensions of Partner Models for Speech Interfaces Using a Psycholexical Approachcited by 3
- 2024Coimagining the Future of Voice Assistants with Cultural Sensitivitycited by 3
- 2021LGBTQ-AI? Exploring Expressions of Gender and Sexual Orientation in Chatbotscited by 2
- 2024LLM-Mediated Domain-Specific Voice Agents: The Case of TextileBotcited by 1
- 2026Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interactioncited by 1
- 2026Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaborationcited by 0
- 2026Humans' ALMANAC: A Human Collaboration Dataset of Action-Level Mental Model Annotations for Agent Collaboration4 Jun 2026
- 2026Human or Machine? A Preliminary Turing Test for Speech-to-Speech Interaction27 Feb 2026
- 2025Toward Metaphor-Fluid Conversation Design for Voice User Interfaces17 Feb 2025
- 2024Designing AI Personalities: Enhancing Human-Agent Interaction Through Thoughtful Persona Design30 Oct 2024
- 2024LLM-Mediated Domain-Specific Voice Agents: The Case of TextileBot15 Jun 2024
- 2024Coimagining the Future of Voice Assistants with Cultural Sensitivity26 Mar 2024
- 2024Understanding Public Perceptions of AI Conversational Agents: A Cross-Cultural Analysis25 Feb 2024
- 2023Impact of Guidance and Interaction Strategies for LLM Use on Learner Performance and Perception13 Oct 2023
- 2021LGBTQ-AI? Exploring Expressions of Gender and Sexual Orientation in Chatbots3 Jun 2021
- 2021What Do We See in Them? Identifying Dimensions of Partner Models for Speech Interfaces Using a Psycholexical Approach3 Feb 2021