Recent work has looked to understand user perceptions of speech agent capabilities as dialogue partners (termed partner models), and how this affects user interaction. Yet, partner model effects are currently inferred from language production as no metrics are available to quantify these subjective perceptions more directly. Through three phases of work, we develop and validate the Partner Modelling Questionnaire (PMQ): an 18-item self-report semantic differential scale designed to reliably measure people’s partner models of non-embodied speech interfaces. Through confirmatory factor analysis, we confirm that the PMQ scale consists of three factors: communicative competence and dependability, human-likeness in communication and communicative flexibility. Our studies show that the measure consistently demonstrates good internal reliability, strong test-retest reliability over 4- and 12-week intervals, and predictable convergent/divergent validity. Based on our findings, we discuss the multidimensional nature of partner models, while identifying key future research avenues that the development of the PMQ facilitates. Notably, this includes the need to identify the activation, sensitivity, and dynamism of partner models in speech interface interaction.

Advances in natural language processing and understanding have led to a rapid growth in the popularity of conversational user interfaces (CUIs). While CUIs introduce novel benefits, they also yield risks that may exploit people’s trust. Although research looking at unethical design deployed through graphical user interfaces (GUIs) established a thorough understanding of so-called dark patterns, there is a need to continue this discourse within the CUI community to understand potentially problematic interactions. Addressing this gap, we interviewed 27 participants from three cohorts: researchers, practitioners, and frequent users of CUIs. Applying thematic analysis, we construct five themes reflecting each cohort’s insights about ethical design challenges and introduce the CUI Expectation Cycle, bridging system capabilities and user expectations while considering each theme’s ethical caveats. This research aims to inform future development of CUIs to consider ethical constraints while adopting a human-centred approach.

Interest in unethical user interfaces has grown in HCI over recent years, with researchers identifying malicious design strategies referred to as “dark patterns”. While such strategies have been described in numerous domains, we lack a thorough understanding of how they operate in social networking services (SNSs). Pivoting towards regulations against such practices, we address this gap by offering novel insights into the types of dark patterns deployed in SNSs and people’s ability to recognise them across four widely used mobile SNS applications. Following a cognitive walkthrough, experts (N = 6) could identify instances of dark patterns in all four SNSs, including co-occurrences. Based on the results, we designed a novel rating procedure for evaluating the malice of interfaces. Our evaluation shows that regular users (N = 193) could differentiate between interfaces featuring dark patterns and those without. Such rating procedures could support policymakers’ current moves to regulate deceptive and manipulative designs in online interfaces.

Research in HCI has shown a growing interest in unethical design practices across numerous domains, often referred to as “dark patterns”. There is, however, a gap in related literature regarding social networking services (SNSs). In this context, studies emphasise a lack of users’ self-determination regarding control over personal data and time spent on SNSs. We collected over 16 hours of screen recordings from Facebook’s, Instagram’s, TikTok’s, and Twitter’s mobile applications to understand how dark patterns manifest in these SNSs. For this task, we turned towards HCI experts to mitigate possible difficulties of non-expert participants in recognising dark patterns, as prior studies have noticed. Supported by the recordings, two authors of this paper conducted a thematic analysis based on previously described taxonomies, manually classifying the recorded material while delivering two key findings: We observed which instances occur in SNSs and identified two strategies — engaging and governing — with five dark patterns undiscovered before.

Casual conversation, where people engage in social talk or phatic communion (Coupland et al., 1992) (i.e., non-task oriented talk) is acknowledged as important in facilitating collaboration among c...

Perceptions of system competence and communicative ability, termed partner models, play a significant role in speech interface interaction. Yet we do not know what the core dimensions of this concept are. Taking a psycholexical approach, our paper is the first to identify the key dimensions that define partner models in speech agent interaction. Through a repertory grid study (N=21), a review of key subjective questionnaires, an expert review of resulting word pairs and an online study of 356 users of speech interfaces, we identify three key dimensions that make up a users’ partner model: 1) perceptions towards partner competence and dependability; 2) assessment of human-likeness; and 3) a system’s perceived cognitive flexibility. We discuss the implications for partner modelling as a concept, emphasising the importance of salience and the dynamic nature of these perceptions.

Limited linguistic coverage for Intelligent Personal Assistants (IPAs) means that many interact in a non-native language. Yet we know little about how IPAs currently support or hinder these users. Through native (L1) and non-native (L2) English speakers interacting with Google Assistant on a smartphone and smart speaker, we aim to understand this more deeply. Interviews revealed that L2 speakers prioritised utterance planning around perceived linguistic limitations, as opposed to L1 speakers prioritising succinctness because of system limitations. L2 speakers see IPAs as insensitive to linguistic needs resulting in failed interaction. L2 speakers clearly preferred using smartphones, as visual feedback supported diagnoses of communication breakdowns whilst allowing time to process query results. Conversely, L1 speakers preferred smart speakers, with audio feedback being seen as sufficient. We discuss the need to tailor the IPA experience for L2 users, emphasising visual feedback whilst reducing the burden of language production.

Conversational agents promise conversational interaction but fail to deliver. Efforts often emulate functional rules from human speech, without considering key characteristics that conversation must encapsulate. Given its potential in supporting long-term human-agent relationships, it is paramount that HCI focuses efforts on delivering this promise. We aim to understand what people value in conversation and how this should manifest in agents. Findings from a series of semi-structured interviews show people make a clear dichotomy between social and functional roles of conversation, emphasising the long-term dynamics of bond and trust along with the importance of context and relationship stage in the types of conversations they have. People fundamentally questioned the need for bond and common ground in agent communication, shifting to more utilitarian definitions of conversational qualities. Drawing on these findings we discuss key challenges for conversational agent design, most notably the need to redefine the design parameters for conversational agent interaction.

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.

Abstract Speech interfaces are growing in popularity. Through a review of 99 research papers this work maps the trends, themes, findings and methods of empirical research on speech interfaces in the field of human–computer interaction (HCI). We find that studies are usability/theory-focused or explore wider system experiences, evaluating Wizard of Oz, prototypes or developed systems. Measuring task and interaction was common, as was using self-report questionnaires to measure concepts like usability and user attitudes. A thematic analysis of the research found that speech HCI work focuses on nine key topics: system speech production, design insight, modality comparison, experiences with interactive voice response systems, assistive technology and accessibility, user speech production, using speech technology for development, peoples’ experiences with intelligent personal assistants and how user memory affects speech interface interaction. From these insights we identify gaps and challenges in speech research, notably taking into account technological advancements, the need to develop theories of speech interface interaction, grow critical mass in this domain, increase design work and expand research from single to multiple user interaction contexts so as to reflect current use contexts. We also highlight the need to improve measure reliability, validity and consistency, in the wild deployment and reduce barriers to building fully functional speech interfaces for research. RESEARCH HIGHLIGHTS Most papers focused on usability/theory-based or wider system experience research with a focus on Wizard of Oz and developed systems Questionnaires on usability and user attitudes often used but few were reliable or validated Thematic analysis showed nine primary research topics Challenges identified in theoretical approaches and design guidelines, engaging with technological advances, multiple user and in the wild contexts, critical research mass and barriers to building speech interfaces