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

In 1950, Alan Turing proposed his concept of universal machines, emphasizing their abilities to learn, think, and behave in a human-like manner. Today, the existence of intelligent agents imitating human characteristics is more relevant than ever. They have expanded to numerous aspects of daily life. Yet, while they are often seen as work simplifiers, their interactions usually lack social competence. In particular, they miss what one may call authenticity. In the study presented in this paper, we explore how characteristics of social intelligence may enhance future agent implementations. Interviews and an open question survey with experts from different fields have led to a shared understanding of what it would take to make intelligent virtual agents, in particular messaging agents (i.e., chat bots), more authentic. Results suggest that showcasing a transparent purpose, learning from experience, anthropomorphizing, human-like conversational behavior, and coherence, are guiding characteristics for agent authenticity and should consequently allow for and support a better coexistence of artificial intelligence technology with its respective users.

The demographic shift marks the beginning of a social transformation with far reaching implications, and differences in aging processes across individuals render one-size fits-all policies ineffective. An area of increasing importance is assistive technology, including physical and Social Assistance Robots (SARs) for elderly support. In order to increase the effectiveness of such technologies, their design, functionality, and acceptance by target users must be evaluated. This paper presents a study that examines SAR technology acceptance among the future elderly (aged 20–60) in a German-speaking population (N=188). In doing this, we investigated the relationships between personality, resilience, technology experience, expectations for technology, fulfilment of expectations for technology, and technology acceptance. The study found significant correlations between age, gender, education, personality, resilience, experience, expectations, and technology acceptance and its subdimensions. Of the personality dimensions, agreeableness and neuroticism were found most relevant. Small effects were found between resilience and acceptance, and highly significant ones between technology acceptance, technology experience, expectations for SARs, and fulfilment of expectations for SARs. In keeping with previous research, the findings suggest that personality plays a significant role in the acceptance of SAR technologies. This study may be one of the first that considers and evaluates resilience as a factor in technology acceptance.

Wizard of Oz (WOZ) is a well-established method for simulating the functionality and user experience of future systems. Using a human wizard to mimic certain operations of a potential system is particularly useful in situations where extensive engineering effort would otherwise be needed to explore the design possibilities offered by such operations. The WOZ method has been widely used in connection with speech and language technologies, but advances in sensor technology and pattern recognition as well as new application areas such as human–robot interaction have made it increasingly relevant to the design of a wider range of interactive systems. In such cases, achieving acceptable performance at the user interface level often hinges on resource-intensive improvements such as domain tuning, which are better done once the overall design is relatively stable. Although WOZ is recognized as a valuable prototyping technique, surprisingly little effort has been put into exploring it from a methodological point of view. Starting from a survey of the literature, this paper presents a systematic investigation and analysis of the design space for WOZ for language technology applications, and proposes a generic architecture for tool support that supports the integration of components for speech recognition and synthesis as well as for machine translation. This architecture is instantiated in WebWOZ—a new web-based open-source WOZ prototyping platform. The viability of generic support is explored empirically through a series of evaluations. Researchers from a variety of backgrounds were able to create experiments, independent of their previous experience with WOZ. The approach was further validated through a number of real experiments, which also helped to identify a number of possibilities for additional support, and flagged potential issues relating to consistency in wizard performance.

The increasing progress in artificial intelligence and respective machine learning technology has fostered the proliferation of chatbots to the point where today they are being embedded into various human-technology interaction tasks. In enterprise contexts, the use of chatbots seeks to reduce labor costs and consequently increase productivity. For simple, repetitive customer service tasks such already proves beneficial, yet more complex collaborative knowledge work seems to require a better understanding of how the technology may best be integrated. Particularly, the additional mental burden which accompanies the use of these natural language based artificial assistants, often remains overlooked. To this end, cognitive load theory implies that unnecessary use of technology can induce additional extrinsic load and thus may have a contrary effect on users’ productivity. The research presented in this paper thus reports on a study assessing cognitive load and productivity implications of human chatbot interaction in a realistic enterprise setting. A/B testing software-only vs. software + chatbot interaction, and the NASA TLX were used to evaluate and compare the cognitive load of two user groups. Results show that chatbot users experienced less cognitive load and were more productive than software-only users. Furthermore, they show lower frustration levels and better overall performance (i.e, task quality) despite their slightly longer average task completion time.