The Character as subjective interface

This paper re-frames virtual interactive characters as " subjective interfaces " with the purpose of highlighting original affordances for interactive story-telling through conversation. This notion is theoretically unpacked in the perspectives of narratology, interaction design and game design. Existing and imagined scenarios are presented in which subjective interfaces are elevated as core interaction mechanics. Finally, technical challenges posed by this approach are reviewed alongside relevant existing research leads.Fonds de Recherche du Québec - Société et Cultur

Innovative online portal to support persons with obesity: STOP Project RCT

Background: This research is part of the STOP project, a H2020 RISE project funded by European Commission (GA No 823978) to address the challenge of preventing obesity in Europe. The interdisciplinary European STOP project aims to establish a data and knowledge ecosystem as a basis for the STOP Portal to enable healthcare professionals in decision support, and persons with obesity in analysis and feedback of health information to optimise healthy nutrition. The aim of this current randomised controlled trial (RCT) was to determine the effectiveness of the newly developed system for adults with overweight and obesity to lose weight. Methods: This was a pilot two-arm RCT: 1. intervention (n = 15) and 2. control (n = 15). All the participants were adults with overweight or obesity. The intervention group used the STOP Portal, while the control group did not use this system, no intervention. Participants were randomised into one of the two groups using a computer randomised programme. The primary outcome was percentage reported weight loss, by three months. Four data collection points for both the intervention and control groups at 1. baseline (month 0); 2. month 1; 3. month 2; and 4. month 3. The STOP Portal collects the following data: physiological data, knowledge resources, biomedical data, self-reporting activity and food data. Ethical approval was obtained. Results: A total of 30 adults registered for this pilot RCT and participated up to three months. The results clearly indicated that adults (18 years+) who were overweight or obese and were in the intervention group and using the STOP Portal significantly (P < 0.001) lost body weight (kg; % weight loss; BMI). Thus the STOP Portal was significantly effective for participants losing body weight. Conclusions: Overall, the STOP Portal is easy to use, fit for purpose and is significantly effective for adults with overweight and obesity to lose weight. Key messages: • Innovative online portal, STOP Portal, is significantly effective for adults with overweight and obesity to lose weight. • This project addresses obesity management and prevention through the foundation of an innovative platform to support persons with obesity with a better nutrition

Recognising facial expressions in video sequences

We introduce a system that processes a sequence of images of a front-facing human face and recognises a set of facial expressions. We use an efficient appearance-based face tracker to locate the face in the image sequence and estimate the deformation of its non-rigid components. The tracker works in real-time. It is robust to strong illumination changes and factors out changes in appearance caused by illumination from changes due to face deformation. We adopt a model-based approach for facial expression recognition. In our model, an image of a face is represented by a point in a deformation space. The variability of the classes of images associated to facial expressions are represented by a set of samples which model a low-dimensional manifold in the space of deformations. We introduce a probabilistic procedure based on a nearest-neighbour approach to combine the information provided by the incoming image sequence with the prior information stored in the expression manifold in order to compute a posterior probability associated to a facial expression. In the experiments conducted we show that this system is able to work in an unconstrained environment with strong changes in illumination and face location. It achieves an 89\% recognition rate in a set of 333 sequences from the Cohn-Kanade data base

Exploring patient information needs in type 2 diabetes: A cross sectional study of questions

This study set out to analyze questions about type 2 diabetes mellitus (T2DM) from patients and the public. The aim was to better understand people's information needs by starting with what they do not know, discovered through their own questions, rather than starting with what we know about T2DM and subsequently finding ways to communicate that information to people affected by or at risk of the disease. One hundred and sixty-four questions were collected from 120 patients attending outpatient diabetes clinics and 300 questions from 100 members of the public through the Amazon Mechanical Turk crowdsourcing platform. Twenty-three general and diabetes-specific topics and five phases of disease progression were identified; these were used to manually categorize the questions. Analyses were performed to determine which topics, if any, were significant predictors of a question's being asked by a patient or the public, and similarly for questions from a woman or a man. Further analysis identified the individual topics that were assigned significantly more often to the crowdsourced or clinic questions. These were Causes (CI: [-0.07, -0.03], p < .001), Risk Factors ([-0.08, -0.03], p < .001), Prevention ([-0.06, -0.02], p < .001), Diagnosis ([-0.05, -0.02], p < .001), and Distribution of a Disease in a Population ([-0.05,-0.01], p = .0016) for the crowdsourced questions and Treatment ([0.03, 0.01], p = .0019), Disease Complications ([0.02, 0.07], p < .001), and Psychosocial ([0.05, 0.1], p < .001) for the clinic questions. No highly significant gender-specific topics emerged in our study, but questions about Weight were more likely to come from women and Psychosocial questions from men. There were significantly more crowdsourced questions about the time Prior to any Diagnosis ([(-0.11, -0.04], p = .0013) and significantly more clinic questions about Health Maintenance and Prevention after diagnosis ([0.07. 0.17], p < .001). A descriptive analysis pointed to the value provided by the specificity of questions, their potential to disclose emotions behind questions, and the as-yet unrecognized information needs they can reveal. Large-scale collection of questions from patients across the spectrum of T2DM progression and from the public-a significant percentage of whom are likely to be as yet undiagnosed-is expected to yield further valuable insights

Is spoken language all-or-nothing? Implications for future speech-based human-machine interaction

Recent years have seen significant market penetration for voice-based personal assistants such as Apple’s Siri. However, despite this success, user take-up is frustratingly low. This article argues that there is a habitability gap caused by the inevitablemismatch between the capabilities and expectations of human users and the features and benefits provided by contemporary technology. Suggestions aremade as to how such problems might be mitigated, but a more worrisome question emerges: “is spoken language all-or-nothing”? The answer, based on contemporary views on the special nature of (spoken) language, is that there may indeed be a fundamental limit to the interaction that can take place between mismatched interlocutors (such as humans and machines). However, it is concluded that interactions between native and non-native speakers, or between adults and children, or even between humans and dogs, might provide critical inspiration for the design of future speech-based human-machine interaction

Developmental course of conversational behaviour of children with 22q11.2 deletion syndrome and Williams syndrome

This study investigated three conversational subskills in children with 22q11.2 deletion syndrome (22q11.2DS, n = 8, ages 7–13) and Williams syndrome (WS, n = 8, ages 6–12). We re-evaluated these subskills after 18 to 24 months and compared them to those of peers with idiopathic intellectual disability (IID) and IID and comorbid autism spectrum disorders (IID+ASD). Children with 22q11.2DS became less actively involved over time. Lower assertiveness than in children with IID was demonstrated. They seemed less impaired in terms of accounting for listener’s knowledge than children with IID+ASD. Children with WS showed greater difficulties with discourse management compared to children with IID and 22q11.2DS. They had similar levels of conversational impairments to children with IID+ASD but these were caused by different shortcomings. Over time taking account of listener’s knowledge became challenging for them. Findings suggest that children with 22q11.2DS and those with WS would benefit from conversational skills support and that regular re-evaluation is needed to anticipate conversational challenges

The MATCH Corpus: A Corpus of Older and Younger Users' Interactions With Spoken Dialogue Systems.

We present the MATCH corpus, a unique data set of 447 dialogues in which 26 older and 24 younger adults interact with nine different spoken dialogue systems. The systems varied in the number of options presented and the confirmation strategy used. The corpus also contains information about the users’ cognitive abilities and detailed usability assessments of each dialogue system. The corpus, which was collected using a Wizard-of-Oz methodology, has been fully transcribed and annotated with dialogue acts and ‘‘Information State Update’’ (ISU) representations of dialogue context. Dialogue act and ISU annotations were performed semi-automatically. In addition to describing the corpus collection and annotation, we present a quantitative analysis of the interaction behaviour of older and younger users and discuss further applications of the corpus. We expect that the corpus will provide a key resource for modelling older people’s interaction with spoken dialogue systems