Connecting Brains and Bodies: Applying Physiological Computing to Support Social Interaction

Physiological and affective computing propose methods to improve human-machine interactions by adapting machines to the users' states. Recently, social signal processing (SSP) has proposed to apply similar methods to human-human interactions with the hope of better understanding and modeling social interactions. Most of the social signals employed are facial expressions, body movements and speech, but studies using physiological signals remain scarce. In this paper, we motivate the use of physiological signals in the context of social interactions. Specifically, we review studies which have investigated the relationship between various physiological indices and social interactions. We then propose two main directions to apply physiological SSP: using physiological signals of individual users as new social cues displayed in the group and using inter-user physiology to measure properties of the interactions such as conflict and social presence. We conclude that physiological measures have the potential to enhance social interactions and to connect peopl

Machines outperform laypersons in recognizing emotions elicited by autobiographical recollection

Over the last decade, an increasing number of studies have focused on automated recognition of human emotions by machines. However, performances of machine emotion recognition studies are difficult to interpret because benchmarks have not been established. In order to provide such a benchmark, we compared machine with human emotion recognition. We gathered facial expressions, speech, and physiological signals from 17 individuals expressing 5 different emotional states. Support vector machines achieved an 82% recognition accuracy based on a physiological and facial features. In experiments with 75 humans on the same data, a maximum recognition accuracy of 62.8% was obtained. As machines outperformed humans, automated emotion recognition might be ready to be tested in more practical applications

Affective Computing

This book provides an overview of state of the art research in Affective Computing. It presents new ideas, original results and practical experiences in this increasingly important research field. The book consists of 23 chapters categorized into four sections. Since one of the most important means of human communication is facial expression, the first section of this book (Chapters 1 to 7) presents a research on synthesis and recognition of facial expressions. Given that we not only use the face but also body movements to express ourselves, in the second section (Chapters 8 to 11) we present a research on perception and generation of emotional expressions by using full-body motions. The third section of the book (Chapters 12 to 16) presents computational models on emotion, as well as findings from neuroscience research. In the last section of the book (Chapters 17 to 22) we present applications related to affective computing

Lost in interpretation: the function of role, question strategies, and emotion in interpreter-assisted investigative interviews

Interpreters enable police to gather key evidentiary information during interviews with victims, witnesses, and suspects who are foreign language speakers. However, words and phrasing in one language do not always have direct interpretations, and interpreted interview evidence can be liable to distortions. To date, as far as is known, an extremely limited body of research has examined the impact interpreters have on the quality and accuracy of interpreter-assisted investigative interviews (IAIIs) and interpreted evidence. This PhD research breaks new ground by examining the impact the presence of an interpreter has on the quality and accuracy of interpreted evidence, both in the interview room and in the courtroom, utilising multiple data sources and methodologies, and highlighting the impact interpreter bias can have on the investigative and prosecution process. Furthermore, this PhD scrutinises how legislation concerning the provision of interpreters has impacted the work of criminal justice interpreters, while exploring explore how trauma and emotion during investigative interviews has further affected interpreted investigative interviews. Previous research has suggested that the interpreter is likely to be a factor influencing the quality of the evidence provided, particularly interpreter emotion, but this has not been explored empirically until now. Results from the four studies in this thesis indicate that discrepancies in police officers’ and interpreters’ expectations during IAIIs can negatively impact the quality of the interview. While both police officers and interpreters recognise emotions as a factor likely to impact the quality of the interview, currently little is done to actively prevent it. Results suggest that highly complex, traumatic crimes increase the likelihood of interpreting errors, which has significant implications for certain major crimes that are likely to involve both foreign language speakers and emotional trauma. Finally, the findings emphasise a lack of understanding on the role, function, and importance of interpreter quality, suggesting a need for changes in government policy regarding public service interpreting and make suggestions for improving interview training for both police officers and interpreters

Unmet goals of tracking: within-track heterogeneity of students' expectations for

Educational systems are often characterized by some form(s) of ability grouping, like tracking. Although substantial variation in the implementation of these practices exists, it is always the aim to improve teaching efficiency by creating homogeneous groups of students in terms of capabilities and performances as well as expected pathways. If students’ expected pathways (university, graduate school, or working) are in line with the goals of tracking, one might presume that these expectations are rather homogeneous within tracks and heterogeneous between tracks. In Flanders (the northern region of Belgium), the educational system consists of four tracks. Many students start out in the most prestigious, academic track. If they fail to gain the necessary credentials, they move to the less esteemed technical and vocational tracks. Therefore, the educational system has been called a 'cascade system'. We presume that this cascade system creates homogeneous expectations in the academic track, though heterogeneous expectations in the technical and vocational tracks. We use data from the International Study of City Youth (ISCY), gathered during the 2013-2014 school year from 2354 pupils of the tenth grade across 30 secondary schools in the city of Ghent, Flanders. Preliminary results suggest that the technical and vocational tracks show more heterogeneity in student’s expectations than the academic track. If tracking does not fulfill the desired goals in some tracks, tracking practices should be questioned as tracking occurs along social and ethnic lines, causing social inequality

Proceedings of EVA London 2024

The Electronic Visualisation and the Arts London 2024 Conference (EVA London 2024) is co-sponsored by the Computer Arts Society (CAS) and BCS, the Chartered Institute for IT, of which the CAS is a Specialist Group. As for 2022, the EVA London 2023 Conference is a physical and online “hybrid” conference. We continue with publishing the proceedings, both online, with open access via ScienceOpen, and also in our traditional printed form, in full colour. The main conference presentations run during 10–13 July 2023, with workshops and other activities, especially for students, on 14 July 2023

Esa 12th Conference: Differences, Inequalities and Sociological Imagination: Abstract Book

Esa 12th Conference: Differences, Inequalities and Sociological Imagination: Abstract Boo