User Modelling and Adaptive, Natural Interaction for Conflict Resolution

Confronting conflicts and coping with them is part of social life, since conflicts seem to arise in almost every context and developmental stage of human life. The personal and collective gains that follow conflict resolution have motivated scholars across many research fields to advocate the use of pro-social mechanisms for resolution. The Siren serious game aims to support teachers' role to educate young people on how to resolve conflicts, by employing user- and cultural adaptivity and affective, non-verbal interaction to provide interesting and relevant conflict scenarios and resolution approaches

Progressive Transformers for End-to-End Sign Language Production

The goal of automatic Sign Language Production (SLP) is to translate spoken language to a continuous stream of sign language video at a level comparable to a human translator. If this was achievable, then it would revolutionise Deaf hearing communications. Previous work on predominantly isolated SLP has shown the need for architectures that are better suited to the continuous domain of full sign sequences. In this paper, we propose Progressive Transformers, a novel architecture that can translate from discrete spoken language sentences to continuous 3D skeleton pose outputs representing sign language. We present two model configurations, an end-to-end network that produces sign direct from text and a stacked network that utilises a gloss intermediary. Our transformer network architecture introduces a counter that enables continuous sequence generation at training and inference. We also provide several data augmentation processes to overcome the problem of drift and improve the performance of SLP models. We propose a back translation evaluation mechanism for SLP, presenting benchmark quantitative results on the challenging RWTH-PHOENIX-Weather-2014T(PHOENIX14T) dataset and setting baselines for future research

Integration of a Spanish-to-LSE machine translation system into an e-learning platform

The final publication is available at Springer via http://dx.doi.org/10.1007/978-3-642-21657-2_61This paper presents the first results of the integration of a Spanish-to-LSE Machine Translation (MT) system into an e-learning platform. Most e-learning platforms provide speech-based contents, which makes them inaccessible to the Deaf. To solve this issue, we have developed a MT system that translates Spanish speech-based contents into LSE. To test our MT system, we have integrated it into an e-learning tool. The e-learning tool sends the audio to our platform. The platform sends back the subtitles and a video stream with the signed translation to the e-learning tool. Preliminary results, evaluating the sign language synthesis module, show an isolated sign recognition accuracy of 97%. The sentence recognition accuracy was of 93%.Authors would like to acknowledge the FPU-UAM grant program for its financial support. Authors are grateful to the FCNSE linguistic department for sharing their knowledge in LSE and performing the evaluations. Many thanks go to María Chulvi and Benjamín Nogal for providing help during the imple-mentation of this system. This work was partially supported by the Telefónica Móviles España S.A. project number 10-047158-TE-Ed-01-1

A randomised controlled trial of the Neuro Emotional Technique (NET) for childhood Attention Deficit Hyperactivity Disorder (ADHD): a protocol

<p>Abstract</p> <p>Background</p> <p>An abundance of literature is dedicated to research for the treatment of Attention Deficit Hyperactivity Disorder (ADHD). Most, is in the area of pharmacological therapies with less emphasis in psychotherapy and psychosocial interventions and even less in the area of complementary and alternative medicine (CAM).</p> <p>The use of CAM has increased over the years, especially for developmental and behavioral disorders, such as ADHD. 60–65% of parents with children with ADHD have used CAM. Medical evidence supports a multidisciplinary approach (i.e. pharmacological and psychosocial) for the best clinical outcomes. The Neuro Emotional Technique (NET), a branch of Chiropractic, was designed to address the biopsychosocial aspects of acute and chronic conditions including non-musculoskeletal conditions. Anecdotally, it has been suggested that ADHD may be managed effectively by NET.</p> <p>Design/methods</p> <p>A placebo controlled, double blind randomised clinical trial was designed to assess the effectiveness of NET on a cohort of children with medically diagnosed ADHD.</p> <p>Children aged 5–12 years who met the inclusion criteria were randomised to one of three groups. The control group continued on their existing medical regimen and the intervention and placebo groups had the addition of the NET and sham NET protocols added to their regimen respectively. These two groups attended a clinical facility twice a week for the first month and then once a month for six months.</p> <p>The Conners' Parent and Teacher Rating Scales (CRS) were used at the start of the study to establish baseline data and then in one month and in seven months time, at the conclusion of the study. The primary outcome measures chosen were the Conners' ADHD Index and Conners' Global Index. The secondary outcome measures chosen were the DSM-IV: Inattentive, the DSM-IV:Hyperactive-Impulsive, and the DSM-IV:Total subscales from the Conners' Rating Scales, monitoring changes in inattention, hyperactivity and impulsivity.</p> <p>Calculations for the sample size were set with a significance level of 0.05 and the power of 80%, yielding a sample size of 93.</p> <p>Discussion</p> <p>The present study should provide information as to whether the addition of NET to an existing medical regimen can improve outcomes for children with ADHD.</p> <p>Trial registration</p> <p>Australian New Zealand Clinical Trial Registration Number: ANZCTRN 012606000332527</p

Visual Focus of Attention in Non-calibrated Environments using Gaze Estimation

Abstract Estimating the focus of attention of a person highly depends on her/his gaze directionality. Here, we propose a new method for estimating visual focus of attention using head rotation, as well as fuzzy fusion of head rotation and eye gaze estimates, in a fully automatic manner, without the need for any special hardware or a priori knowledge regarding the user, the environment or the setup. Instead, we propose a system aimed at functioning under unpretending conditions, only with the usage of simple hardware, like a normal web-camera. Our system is aimed at functioning in a human-computer interaction environment, considering a person is facing a monitor with a camera adjusted on top. To this aim, we propose in this paper two novel techniques, based on local and appearance information, estimating head rotation, and we adaptively fuse them in a common framework. The system is able to recognize head rotational movement, under translational movements of the user towards any direction, without any knowledge or a-priori estimate of the user&apos;s distance from the camera or camera intrinsic parameters