activity
20192024
most citedWhat Makes a Good Conversation? Challenges in Designing Truly Conversational Agents

457 citations · 740 across the 17 of their papers we have counts for

collaborators

18 papers

cs.HC2024

Comparing Perceptions of Static and Adaptive Proactive Speech Agents

Justin Edwards, Philip R. Doyle, Holly P. Branigan +1

A growing literature on speech interruptions describes how people interrupt one another with speech, but these behaviours have not yet been implemented in the design of artificial…

cs.HC2023★ 10 cited

The Partner Modelling Questionnaire: A validated self-report measure of perceptions toward machines as dialogue partners

Philip R. Doyle, Iona Gessinger, Justin Edwards +7

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, current…

cs.HC2022★ 1 cited

Embrace your incompetence! Designing appropriate CUI communication through an ecological approach

Sophie Becker, Philip Doyle, Justin Edwards

People form impressions of their dialogue partners, be they other people or machines, based on cues drawn from their communicative style. Recent work has suggested that the gulf be…

cs.HC2022★ 5 cited

Bilingual by default: Voice Assistants and the role of code-switching in creating a bilingual user experience

Helin Cihan, Yunhan Wu, Paola Peña +2

Conversational User Interfaces such as Voice Assistants are hugely popular. Yet they are designed to be monolingual by default, lacking support for, or sensitivity to, the bilingua…

cs.HC2021

Alexa, Play Fetch! A Review of Alexa Skills for Pets

Justin Edwards, Orla Cooney, Rachel Edwards

Alexa Skills are used for a variety of daily routines and purposes, but little research has focused on a key part of many people's daily lives: their pets. We present a systematic…

cs.HC2021★ 5 cited

CUI @ Auto-UI: Exploring the Fortunate and Unfortunate Futures of Conversational Automotive User Interfaces

Justin Edwards, Philipp Wintersberger, Leigh Clark +6

This work aims to connect the Automotive User Interfaces (Auto-UI) and Conversational User Interfaces (CUI) communities through discussion of their shared view of the future of aut…

cs.HC2021★ 2 cited

Bridging Social Distance During Social Distancing: Exploring Social Talk and Remote Collegiality in Video Conferencing

Anna Bleakley, Daniel Rough, Justin Edwards +6

Video conferencing systems have long facilitated work-related conversations among remote teams. However, social distancing due to the COVID-19 pandemic has forced colleagues to use…

cs.HC2021

Eliciting Spoken Interruptions to Inform Proactive Speech Agent Design

Justin Edwards, Christian Janssen, Sandy Gould +1

Current speech agent interactions are typically user-initiated, limiting the interactions they can deliver. Future functionality will require agents to be proactive, sometimes inte…

cs.HC2021★ 8 cited

LGBTQ-AI? Exploring Expressions of Gender and Sexual Orientation in Chatbots

Justin Edwards, Leigh Clark, Allison Perrone

Chatbots are popular machine partners for task-oriented and social interactions. Human-human computer-mediated communication research has explored how people express their gender a…

cs.HC2020★ 24 cited

Mental Workload and Language Production in Non-Native Speaker IPA Interaction

Yunhan Wu, Justin Edwards, Orla Cooney +5

Through proliferation on smartphones and smart speakers, intelligent personal assistants (IPAs) have made speech a common interaction modality. Yet, due to linguistic coverage and…

cs.HC2020★ 46 cited

See what I'm saying? Comparing Intelligent Personal Assistant use for Native and Non-Native Language Speakers

Yunhan Wu, Daniel Rough, Anna Bleakley +5

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 hin…

cs.HC2020★ 12 cited

Transparency in Language Generation: Levels of Automation

Justin Edwards, Allison Perrone, Philip R. Doyle

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 r…

cs.HC2019★ 90 cited

Mapping Perceptions of Humanness in Speech-Based Intelligent Personal Assistant Interaction

Philip R. Doyle, Justin Edwards, Odile Dumbleton +2

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 interfa…

cs.HC2019★ 6 cited

Multitasking with Alexa Multitasking with Alexa: How Using Intelligent Personal Assistants Impacts Language-based Primary Task Performance

Justin Edwards, He Liu, Tianyu Zhou +4

Intelligent personal assistants (IPAs) are supposed to help us multitask. Yet the impact of IPA use on multitasking is not clearly quantified, particularly in situations where prim…

cs.HC2019★ 44 cited

What's in an accent? The impact of accented synthetic speech on lexical choice in human-machine dialogue

Benjamin R. Cowan, Philip Doyle, Justin Edwards +5

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…

cs.HC2019★ 22 cited

A Need for Trust in Conversational Interface Research

Justin Edwards, Elaheh Sanoubari

Across several branches of conversational interaction research including interactions with social robots, embodied agents, and conversational assistants, users have identified trus…

cs.HC2019★ 8 cited

Chatbots as Unwitting Actors

Allison Perrone, Justin Edwards

Chatbots are popular for both task-oriented conversations and unstructured conversations with web users. Several different approaches to creating comedy and art exist across the fi…

cs.HC2019★ 457 cited

What Makes a Good Conversation? Challenges in Designing Truly Conversational Agents

Leigh Clark, Nadia Pantidi, Orla Cooney +8

Conversational agents promise conversational interaction but fail to deliver. Efforts often emulate functional rules from human speech, without considering key characteristics that…