Orla Cooney's research while affiliated with University College Dublin and other places

Publications (9)

Article
Full-text available
The unmet need for mental health treatment has motivated considerable research on the design and evaluation of pervasive technology to support people’s mental health. An enduring idea is the use of conversation-based interfaces to deliver mental health support, which is now a realistic prospect given their widespread use in consumer devices. The ub...
Preprint
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 review categorizing the purposes of 88 Alexa Skills aimed at pets and pet owners and introduce a veterinary perspective to assess their benefits and risks. We present 8 t...
Preprint
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 m...
Preprint
Through proliferation on smartphones and smart speakers, intelligent personal assistants (IPAs) have made speech a common interaction modality. Yet, due to linguistic coverage and varying levels of functionality, many speakers engage with IPAs using a non-native language. This may impact the mental workload and pattern of language production displa...
Preprint
Full-text available
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...

Citations

... Wu et. al [17] approach this issue with almost the same motivation i.e., to comprehend and analyze the experience of non-native English ASR systems users against those native English systems users. Their quantitative investigation involves assigning 12 basic, day-to-day tasks to 32 users -14 female and 18 males, equally split into native and non-native English speakers and having each participant document their interactions with the Google Assistant agent, accessed either through smartphone and/or smart speaker. ...
... Pradhan et al. (2020) identifies the need for resources in the IVA with memory support (for example, timers, reminders) for elderly users. Wu et al. (2020), went beyond phonetic issues by analysing the patterns of language production used by native and non-native English speakers. To assess language production in interaction, user task commands were transcribed and number of measures were derived such as number of commands per task, lexical complexity, lexical diversity per task, dynamic lexical adaptation, lexical adaption from initial command. ...
... Our findings offer important design implications which can help to advance recent research trends in the HCI community regarding smart speaker interaction design [13,14]. Specifically, these findings can extend interaction models currently supported by smart speakers. ...