Are you there? : Presence in collaborative distance work

doi linkki ei toimi 31.1.2022, ilmoitettu lehteen/USAlready before the pandemic, digitally mediated collaborative work and communication were perceived as challenging. We investigate the attitudes towards emerging technologies and for transforming practises in workplaces. The focus lies on understanding the readiness for appropriating emotional tracking on presence and support for collaboration. The research-based design framework allowed to combine the various perspectives of the transdisciplinary team. Methods included participatory design, design thinking, contextual inquiry and prototype testing for enhancing presence while working with shared objects in video conferencing to explore the appropriation of tools. The findings revealed four indications: 1) awareness of interlocutors’ presence during synchronous communication is crucial. 2) Emotion and behaviour tracking raises concerns about privacy and personal control over what is displayed to others, and technology could be simpler non-distracting the work at hand. 3) The prototype was found to enhance the feeling of presence without disturbing work at hand, and 4) appropriation requires a step-by-step approach.Peer reviewe

Cognitive visual tracking and camera control

Cognitive visual tracking is the process of observing and understanding the behaviour of a moving person. This paper presents an efficient solution to extract, in real-time, high-level information from an observed scene, and generate the most appropriate commands for a set of pan-tilt-zoom (PTZ) cameras in a surveillance scenario. Such a high-level feedback control loop, which is the main novelty of our work, will serve to reduce uncertainties in the observed scene and to maximize the amount of information extracted from it. It is implemented with a distributed camera system using SQL tables as virtual communication channels, and Situation Graph Trees for knowledge representation, inference and high-level camera control. A set of experiments in a surveillance scenario show the effectiveness of our approach and its potential for real applications of cognitive vision

Absence of spontaneous action anticipation by false belief attribution in children with autism spectrum disorder

Recently, a series of studies demonstrated false belief understanding in young children through completely nonverbal measures. These studies have revealed that children younger than 3 years of age, who consistently fail the standard verbal false belief test, can anticipate others' actions based on their attributed false beliefs. The current study examined whether children with autism spectrum disorder (ASD), who are known to have difficulties in the verbal false belief test, may also show such action anticipation in a nonverbal false belief test. We presented video stimuli of an actor watching an object being hidden in a box. The object was then displaced while the actor was looking away. We recorded children's eye movements and coded whether they spontaneously anticipated the actor's subsequent behavior, which could only have been predicted if they had attributed a false belief to her. Although typically developing children correctly anticipated the action, children with ASD failed to show such action anticipation. The results suggest that children with ASD have an impairment in false belief attribution, which is independent of their verbal ability

Embedding Robotic Agents in the Social Environment

This paper discusses the interactive vision approach, which advocates using knowledge from the human sciences on the structure and dynamics of human-human interaction in the development of machine vision systems and interactive robots. While this approach is discussed generally, the particular case of the system being developed for the Aurora project (which aims to produce a robot to be used as a tool in the therapy of children with autism) is especially considered, with description of the design of the machine vision system being employed and discussion of ideas from the human sciences with particular reference to the Aurora system. An example architecture for a simple interactive agent, which will likely form the basis for the first implementation of this system, is briefly described and a description of hardware used for the Aurora system is given.Peer reviewe

Learning Behavioural Context

The original publication is available at www.springerlink.co

Readers’ cognitive processes during IELTS reading tests: evidence from eye tracking

The research described in this report investigates readers' mental processes as they complete onscreen IELTS (International English Language Testing System) reading test items. It employs up-to-date eye tracking technology to research readers' eye movements and aims, among other things, to contribute to an understanding of the cognitive validity of reading test items (Glaser. 1991; Field forthcoming). Participants were a group of Malaysian undergraduates (n=71) taking an onscreen test consisting of two IELTS reading passages with a total of 11 test items. The eye movements of a random sample of these participants (n=38) were tracked. Questionnaire and stimulated recall interview data were also collected, and were important in order to interpret and explain the eye tracking data. Findings demonstrated significant differences between successful and unsuccessful test-takers on a number of dimensions, including their ability to read expeditiously (Khalifa and Weir. 2009). and their focus on particular aspects of the test items and the reading texts. This demonstrates the potential of eye tracking, in combination with post- hoc interview and questionnaire data, to offer new insights into the cognitive processes of successful and unsuccessful candidates in a reading test. It also gives unprecedented insights into the cognitive processing of successful and unsuccessful readers doing language tests. As a consequence, the findings should be of value to teachers and learners, and also to examination boards seeking to validate and prepare reading tests, as well as psycholinguists and others interested in the cognitive processes of readers

Enhanced associations with actions of the artist influence gaze behaviour

The aesthetic experience of the perceiver of art has been suggested to relate to the art-making process of the artist. The artist’s gestures during the creation process have been stated to influence the perceiver’s art-viewing experience. However, limited studies explore the art-viewing experience in relation to the creative process of the artist. We introduced eye-tracking measures to further establish how congruent actions with the artist influence perceiver’s gaze behaviour. Experiments 1 and 2 showed that simultaneous congruent and incongruent actions do not influence gaze behaviour. However, brushstroke paintings were found to be more pleasing than pointillism paintings. In Experiment 3, participants were trained to associate painting actions with hand primes to enhance visuomotor and visuovisual associations with the artist’s actions. A greater amount of time was spent fixating brushstroke paintings when presented with a congruent prime compared with an incongruent prime, and fewer fixations were made to these styles of paintings when presented with an incongruent prime. The results suggest that explicit links that allow perceivers to resonate with the artist’s actions lead to greater exploration of preferred artwork styles

Frames: A Corpus for Adding Memory to Goal-Oriented Dialogue Systems

This paper presents the Frames dataset (Frames is available at http://datasets.maluuba.com/Frames), a corpus of 1369 human-human dialogues with an average of 15 turns per dialogue. We developed this dataset to study the role of memory in goal-oriented dialogue systems. Based on Frames, we introduce a task called frame tracking, which extends state tracking to a setting where several states are tracked simultaneously. We propose a baseline model for this task. We show that Frames can also be used to study memory in dialogue management and information presentation through natural language generation