Now showing 1 - 4 of 4
  • Publication
    Using Speech to Interrupt Complex Tasks
    (University College Dublin. School of Information and Communication Studies, 2023)
    Interacting with computers using speech promises the benefit of multitasking while one’s hands and eyes are occupied by another task. Users of spoken dialogue sys- tems have not seen this technology as living up to its potential however, in part be- cause speech agents interactions largely behave like traditional interface interactions, initiated by the user. In order to harness the full multitasking benefit of speech as an interaction modality, speech agents must interactive proactively, but doing so means that agents will need to interrupt users engaged in other tasks. While general guide- lines have been proposed for the design of proactive agents in general, the design of proactive speech which interrupts has not been explored in specific. Interrupting speech from proactive agents can take design inspiration from the ways people use speech to interrupt other people, but human speech interruptions are likewise not well understood. The first study of this thesis uses a mixed methods approach to investi- gate the effect of the urgency on people’s timing and strategies for interrupting with speech. The second study complements that data by comparing the effect of urgency on interruption timings and strategies to the effect of the difficulty of the task which is interrupted. The third study uses a data-driven approach to classify the interruptible moments of a complex task in order to analyse the extent to which participants from the prior studies utilised these dynamic characteristics of the ongoing task to shape their interruptions. Finally, the fourth study applies findings from human speech inter- ruption to the design of a proactive agent to investigate the effects of human-inspired adaptivity to context on people’s perceptions of a proactive speech agent. Findings suggest that human speech interruptions are highly diverse and adaptive to context, but such adaptivity may be seen as inappropriate and inconsistent when applied to a speech agent. The implications of this research and its limitations are discussed in the closing chapter.
  • Publication
    Mapping Theoretical and Methodological Perspectives for Understanding Speech Interface Interactions
    The use of speech as an interaction modality has grown considerably through the integration of Intelligent Personal Assistants (IPAs- e.g. Siri, Google Assistant) into smartphones and voice based devices (e.g. Amazon Echo). However, there remain significant gaps in using theoretical frameworks to understand user behaviours and choices and how they may applied to specific speech interface interactions. This part-day multidisciplinary workshop aims to critically map out and evaluate the- oretical frameworks and methodological approaches across a number of disciplines and establish directions for new paradigms in understanding speech interface user behaviour. In doing so, we will bring together participants from HCI and other speech related domains to establish a cohesive, diverse and collaborative community of researchers from academia and industry with interest in exploring theoretical and methodological issues in the field.
    Scopus© Citations 7  569
  • Publication
    Transparency in Language Generation: Levels of Automation
    Language models and conversational systems are growing increasingly advanced, creating outputs that may be mistaken for humans. Consumers may thus be misled by advertising, media reports, or vagueness regarding the role of automation in the production of language. We propose a taxonomy of language automation, based on the SAE levels of driving automation, to establish a shared set of terms for describing automated language. It is our hope that the proposed taxonomy can increase transparency in this rapidly advancing field.
      13Scopus© Citations 4
  • Publication
    What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents
    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.
    Scopus© Citations 249  1019