Exploiting operating system services to efficiently checkpoint parallel applications in GENESIS

Recent research efforts of parallel processing on non-dedicated clusters have focused on high execution performance, parallelism management, transparent access to resources, and making clusters easy to use. However, as a collection of independent computers used by multiple users, clusters are susceptible to failure. This paper shows the development of a coordinated checkpointing facility for the GENESIS cluster operating system. This facility was developed by exploiting existing operating system services. High performance and low overheads are achieved by allowing the processes of a parallel application to continue executing during the creation of checkpoints, while maintaining low demands on cluster resources by using coordinated checkpointing.<br /

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

Through proliferation on smartphones and smart speakers, intel- ligent personal assistants (IPAs) have made speech a common in- teraction modality. Yet, due to linguistic coverage and varying lev- els of functionality, many speakers engage with IPAs using a non- native language. This may impact the mental workload and pat- tern of language production displayed by non-native speakers. We present a mixed-design experiment, wherein native (L1) and non- native (L2) English speakers completed tasks with IPAs through smartphones and smart speakers. We found significantly higher mental workload for L2 speakers during IPA interactions. Contrary to our hypotheses, we found no significant differences between L1 and L2 speakers in terms of number of turns, lexical complexity, diversity, or lexical adaptation when encountering errors. These findings are discussed in relation to language production and pro- cessing load increases for L2 speakers in IPA interaction

See What I’m Saying? Comparing Intelligent Personal Assistant Use for Native and Non-Native Language Speakers

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

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

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 automotive conversational user interfaces. The workshop aims to encourage creative consideration of optimistic and pessimistic futures, encouraging attendees to explore the opportunities and barriers that lie ahead through a game. Considerations of the future will be mapped out in greater detail through the drafting of research agendas, by which attendees will get to know each other's expertise and networks of resources. The two day workshop, consisting of two 90-minute sessions, will facilitate greater communication and collaboration between these communities, connecting researchers to work together to influence the futures they imagine in the workshop.Comment: Workshop published and presented at Automotive User Interfaces 2021 (AutoUI 21

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

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, currently partner model effects are inferred from language production as no metrics are available to quantify these subjective perceptions more directly. Through three studies, 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 principal component analysis and confirmatory factor analysis, we show 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 12 and 4-week intervals, and predictable convergent/divergent validity. Based on our findings we discuss the multidimensional nature of partner models, whilst 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.Comment: Submitted (TOCHI

CUI@IUI: Theoretical and Methodological Challenges in Intelligent Conversational User Interface Interactions

This workshop aims to bring together the Intelligent User Inter- face (IUI) and Conversational User Interface (CUI) communities to understand the theoretical and methodological challenges in designing, deploying and evaluating CUIs. CUIs have continued to prosper with the increased use and technological developments in both text-based chatbots and speech-based systems. However, challenges remain in creating established theoretical and method- ological approaches for CUIs, and how these can be used with recent engineering advances. These include assessing the impact of inter- face design on user behaviours and perceptions, developing design guidelines, understanding the role of personalisation and issues of ethics and privacy. Our half-day multidisciplinary workshop brings together researchers and practitioners from the IUI and CUI communities in academia and industry. We aim to (1) identify and map out key focus areas and research challenges to address these critical theoretical and methodological gaps and (2) foster strong relationships between disciplines within and related to Artificial Intelligence (AI) and Human-Computer Interaction (HCI)

The development of an efficient checkpointing facility exploiting operating systems services of the GENESIS cluster operating system

Recent research efforts of parallel processing on non-dedicated clusters have focused on high execution performance, parallelism management, transparent access to resources, and making clusters easy to use. However, as a collection of independent computers used by multiple users, clusters are susceptible to failure. This paper shows the development of a coordinated checkpointing facility for the GENESIS cluster operating system. This facility was developed by exploiting existing operating system services. High performance and low overheads are achieved by allowing the processes of a parallel application to continue executing during the creation of checkpoints, while maintaining low demands on cluster resources by using coordinated checkpointing.<br /