This paper presents an exploration of how UK radiologists interact with VUI systems and peripherals when authoring diagnostic reports. We conducted a laboratory study with 10 practicing clinical radiologists to investigate the ways in which radiologists utilise speech-based technology to construct, edit and proof their work by having them report on real-world anonymised medical studies on camera. A sample of the participants also participated in interviews in which their data was collaboratively analysed and examined to offer deeper insight into the realism and generalisability of our findings and conclusions. We conclude that better training should be given to radiologists on how VUI systems work, and further investigation should be carried out on the best ways to interact with Speech To Text systems in safety critical environments.

Cycling continues to grow in popularity, both as a means to commute and for exercise. While there is a plethora of research studying technology use in vehicular travel, cycling remains a relatively understudied area—especially within HCI. We conducted an ethnography, adopting an ethnomethodological lens, to study cyclists as they use their bicycles for routine purposes. Through the use of a handlebar-mounted 360-degree action video camera, we conducted our study longitudinally with participants over a number of weeks. Our analysis explicates our participants accountable use of different electronic technologies while on the go and in this paper we present four fragments of their use of different technologies as exemplars from our corpus. Our paper offers insights into the use of technology on bicycles, including how cyclists select moments of opportunity to use technology for different purposes. We conclude by offering design implications for the design of interactive technologies for cyclists.

Speech-enabled smart speakers are common devices used for numerous tasks in everyday life. While speech-enabled technologies are widespread, using one’s voice as a computing modality introduces new accessibility challenges for people with speech disfluencies such as stammering (also known as stuttering). This paper investigates the smart speaker user experiences of people who stammer over three weeks. We conducted diary studies and semi-structured interviews with 11 individuals to identify their daily routines, difficulties with successful interactions, and strategies to overcome these barriers. Our analysis demonstrates key factors such as device location, its affordances, and the structure of commands had a strong impact on user experience. Participants highlighted different linguistic strategies to try and overcome interaction difficulties and discussed the potential of using smart speakers for speech and language therapy. We emphasise the need to further understand the experiences of people who stammer in smart speaker design to increase their accessibility.

Voice-based Conversational Agents (CAs) are increasingly being used by children. Through a review of 38 research papers, this work maps trends, themes, and methods of empirical research on children and CAs in HCI research over the last decade. A thematic analysis of the research found that work in this domain focuses on seven key topics: ascribing human-like qualities to CAs, CAs? support of children?s learning, the use and role of CAs in the home and family context, CAs? support of children?s play, children?s storytelling with CA, issues concerning the collection of information revealed by CAs, and CAs designed for children with differing abilities. Based on our findings, we identify the needs to account for children’s intersectional identities and linguistic and cultural diversity and theories from multiple disciples in the design of CAs, develop heuristics for child-centric interaction with CAs, to investigate implications of CAs on social cognition and interpersonal relationships, and to examine and design for multi-party interactions with CAs for different domains and contexts.

Access to healthcare advice is crucial to promote healthy societies. Many factors shape how access might be constrained, such as economic status, education or, as the COVID-19 pandemic has shown, remote consultations with health practitioners. Our work focuses on providing pre/post-natal advice to maternal women. A salient factor of our work concerns the design and deployment of embodied conversation agents (ECAs) which can sense the (health) literacy of users and adapt to scaffold user engagement in this setting. We present an account of a Wizard of Oz user study of 'ALTCAI', an ECA with three modes of interaction (i.e., adaptive speech and text, adaptive ECA, and non-adaptive ECA). We compare reported engagement with these modes from 44 maternal women who have differing levels of literacy. The study shows that a combination of embodiment and adaptivity scaffolds reported engagement, but matters of health-literacy and language introduce nuanced considerations for the design of ECAs.

The Wizard of Oz method is an increasingly common practice in HCI and CSCW studies as part of iterative design processes for interactive systems. Instead of designing a fully-fledged system, the 'technical work' of key system components is completed by human operators yet presented to study participants as if computed by a machine. However, little is known about how Wizard of Oz studies are interactionally and collaboratively achieved in situ by researchers and participants. By adopting an ethnomethodological perspective, we analyse our use of the method in studies with a voice-controlled vacuum robot and two researchers present. We present data that reveals how such studies are organised and presented to participants and unpack the coordinated orchestration work that unfolds 'behind the scenes' to complete the study. We examine how the researchers attend to participant requests and technical breakdowns, and discuss the performative, collaborative, and methodological nature of their work. We conclude by offering insights from our application of the approach to others in the HCI and CSCW communities for using the method.

Predictions of people's behaviour increasingly drive interactions with a new generation of IoT services designed to support everyday life in the home, from shopping to heating. Based on the premise that such automation is difficult due to the contingent nature of people's practices, in this work we explore the nature of these contingencies in depth. We have designed and conducted a technology probe that made use of simple linear predictions as a provocation, and invited people to track the life of their household essentials over a two-month period. Through a mixed-method approach we demonstrate the challenges of simple predictions, and in turn identify eight categories of contingencies that influenced prediction accuracy. We discuss strategies for how designers of future predictive IoT systems may take the contingencies into account by removing, hiding, revealing, managing, or exploiting the system uncertainty at the core of the issue.

Voice User Interfaces (VUIs) are becoming ubiquitously available, being embedded both into everyday mobility via smartphones, and into the life of the home via 'assistant' devices. Yet, exactly how users of such devices practically thread that use into their everyday social interactions remains underexplored. By collecting and studying audio data from month-long deployments of the Amazon Echo in participants' homes-informed by ethnomethodology and conversation analysis-our study documents the methodical practices of VUI users, and how that use is accomplished in the complex social life of the home. Data we present shows how the device is made accountable to and embedded into conversational settings like family dinners where various simultaneous activities are being achieved. We discuss how the VUI is finely coordinated with the sequential organisation of talk. Finally, we locate implications for the accountability of VUI interaction, request and response design, and raise conceptual challenges to the notion of designing 'conversational' interfaces.

In this paper we unpack the use of conversational agents, or so-called intelligent personal assistants (IPAs), in multi-party conversation amongst a group of friends while they are socialising in a café. IPAs such as Siri or Google Now can be found on a large proportion of personal smartphones and tablets, and are promoted as 'natural language' interfaces. The question we pursue here is how they are actually drawn upon in conversational practice? In our work we examine the use of these IPAs in a mundane and common-place setting and employ an ethnomethodological perspective to draw out the character of the IPA-use in conversation. Additionally, we highlight a number of nuanced practicalities of their use in multi-party settings. By providing a depiction of the nature and methodical practice of their use, we are able to contribute our findings to the design of IPAs.

We present the findings from a study of how people interleave mobile phone use with conversation in pubs. Our findings, informed by ethnomethodology and conversation analysis, unpack the interactional methods through which groups of people in pubs occasioned, sustained, and disengaged from mobile device use during conversation with friends. Fundamentally, the work that is done consists of various methods of accounting for mobile device use, and displaying involvement in social interaction while the device is used. We highlight multiple examples of the nuanced ways in which interleaving is problematic in interaction, and relate our findings to the CSCW and HCI literature on collocated interaction. We conclude by considering avenues for future research, and discuss how we may support or disrupt interleaving practices through design to overcome the highlighted interactional troubles.

The Think Aloud Protocol (TAP) is a verbalisation technique widely employed in HCI user studies to give insight into user experience, yet little work has explored the impact that TAPs have on participants during user studies. This paper utilises a brain sensing technique, fNIRS, to observe the effect that TAPs have on participants. Functional Near-Infrared Spectroscopy (fNIRS) is a brain sensing technology that offers the potential to provide continuous, detailed insight into brain activity, enabling an objective view of cognitive processes during complex tasks. Participants were asked to perform a mathematical task under 4 conditions: nonsense verbalisations, passive concurrent think aloud protocol, invasive concurrent think aloud protocol, and a baseline of silence. Subjective ratings and performance measures were collected during the study. Our results provide a novel view into the effect that different forms of verbalisation have on workload during tasks. Further, the results provide a means for estimating the effect of spoken artefacts when measuring workload, which is another step towards our goal of proactively involving fNIRS analysis in ecologically valid user studies.