The State of Speech in HCI: Trends, Themes and Challenges

Proceedings of the 21st International Conference on Human-Computer Interaction With Mobile Devices and Services

Dumbleton

et al. 2019

Self Cite

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.

Section: Limitations and Future Workmentioning

confidence: 99%

Mapping Perceptions of Humanness in Intelligent Personal Assistant Interaction

Doyle

Proceedings of the 21st International Conference on Human-Computer Interaction With Mobile Devices and Services

Dumbleton

et al. 2019

Self Cite

“…Analyses like these may be particularly useful in quickly measuring trust for conversational agents deployed over the web like commercial IPAs and chatbots. Combining subjective, behavioral, and physiological measures of trust not only enrich the mixed methods approach proposed here for studying trust, but they may also, in combination, allow for creation of robust validated measures which are lacking in conversational HCI in general [2].…”

Section: Measuring Trustmentioning

confidence: 99%

A need for trust in conversational interface research

Proceedings of the 1st International Conference on Conversational User Interfaces

Sanoubari

2019

Self Cite

Across several branches of conversational interaction research including interactions with social robots, embodied agents, and conversational assistants, users have identified trust as a critical part of those interactions. Nevertheless, there is little agreement on what trust means within these sort of interactions or how trust can be measured. In this paper, we explore some of the dimensions of trust as it has been understood in previous work and we outline some of the ways trust has been measured in the hopes of furthering discussion of the concept across the field. CCS CONCEPTS• Human-centered computing → HCI theory, concepts and models; Interaction design theory, concepts and paradigms; User centered design.

“…With speech widely used as a primary interface modality in a number of applications and devices (e.g. Siri, Google Assistant, Amazon Echo) it is imperative that we develop an understanding of the mechanisms that drive language choices in HMD interactions [13]. Here we explore how a dimension of humanness, namely accent, may act as a cue to partner modeling and how this in turn may impact language choices in HMD.…”

Section: Introductionmentioning

confidence: 99%

What's in an accent?

Cowan

Doyle

Proceedings of the 1st International Conference on Conversational User Interfaces

et al. 2019

Self Cite

The assumptions we make about a dialogue partner's knowledge and communicative ability (i.e. our partner models) can influence our language choices. Although similar processes may operate in human-machine dialogue, the role of design in shaping these models, and their subsequent effects on interaction are not clearly understood. Focusing on synthesis design, we conduct a referential communication experiment to identify the impact of accented speech on lexical choice. In particular, we focus on whether accented speech may encourage the use of lexical alternatives that are relevant to a partner's accent, and how this is may vary when in dialogue with a human or machine. We find that people are more likely to use American English terms when speaking with a US accented partner than an Irish accented partner in both human and machine conditions. This lends support to the proposal that synthesis design can influence partner perception of lexical knowledge, which in turn guide user's lexical choices. We discuss the findings with relation to the nature and dynamics of partner models in human machine dialogue.