Perceived Appropriateness: A Novel View for Remediating Perceived Inappropriate Robot Navigation Behaviors

Robots navigating in social environments inevitably exhibit behavior perceived as inappropriate by people, which they will repeat unless they are aware of them; hindering their social acceptance. This highlights the importance of robots detecting and adapting to the perceived appropriateness of their behavior, in line with what we found in a...

Towards creating a conversational memory for long-term meeting support: predicting memorable moments in multi-party conversations through eye-gaze

When working in a group, it is essential to understand each other's viewpoints to increase group cohesion and meeting productivity. This can be challenging in teams: participants might be left misunderstood and the discussion could be going around in circles. To tackle this problem, previous research on group interactions has addressed topics...

The 4th Workshop on Modeling Socio-Emotional and Cognitive Processes from Multimodal Data In-the-Wild (MSECP-Wild)

The ability to automatically infer relevant aspects of human users' thoughts and feelings is crucial for technologies to adapt their behaviors in complex interactions intelligently (e.g., social robots or tutoring systems). Research on multimodal analysis has demonstrated the potential of technology to provide such estimates for a broad range...

Designing Hybrid Intelligence Techniques for Facilitating Collaboration Informed by Social Science

Designing (socially) intelligent systems for facilitating collaborations in human-human and human-AI teams will require them to have a basic understanding of principles underlying social decision-making. Partner selection - the ability to identify and select suitable partners for collaborative relationships - is one relevant component of...

Recognizing Perceived Interdependence in Face-to-Face Negotiations through Multimodal Analysis of Nonverbal Behavior

Enabling computer-based applications to display intelligent behavior in complex social settings requires them to relate to important aspects of how humans experience and understand such situations. One crucial driver of peoples' social behavior during an interaction is the interdependence they perceive, i.e., how the outcome of an interaction...

Social Signals and Multimedia: Past, Present, Future

The rising popularity of Artificial Intelligence (AI) has brought considerable public interest as well faster and more direct transfer of research ideas into practice. One of the aspects of AI that still trails behind considerably is the role of machines in interpreting, enhancing, modeling, generating, and influencing social behavior. Such...

Towards an Engagement-Aware Attentive Artificial Listener for Multi-Party Interactions

Listening to one another is essential to human-human interaction. In fact, we humans spend a substantial part of our day listening to other people, in private as well as in work settings. Attentive listening serves the function to gather information for oneself, but at the same time, it also signals to the speaker that he/she is being heard....

Conversation Quality: Modeling in Free-Standing Conversational Groups

Social interactions in general are multifaceted and there exists an wide set of factors and events that influence them. Hence, interactions as a social phenomena have been studied by researchers in the fields of psychology and social signal processing from different stand points. The common trend in literature is to perform an in-depth study on...

Detecting Emerging Challenges in Social Sidewalk Navigation

When mobile urban robots will share the sidewalk with people, the resulting interactions can cause unexpected undesirable outcomes to emerge – from people running away scared to people deliberately teasing and harassing such systems. How can we design such AI systems to aptly handle the unexpected? Directly anticipating and/or detecting these...

Expressive/Sensitive: Full day workshop at DIS 2020

Our interactions form an intricate 'dance' - a dance requiring a fluent integration of both expressivity (e.g. to approach someone) and sensitivity (e.g. detect if you 'should' approach someone). Work on behaving artefacts has focused mostly on the social, emotional and aesthetic qualities that can be evoked - expressed - through interactions...

Workshop on Interdisciplinary Insights into Group and Team Dynamics

There has been gathering momentum over the last 10 years in the study of group behavior in multimodal multiparty interactions. While many works in the computer science community focus on the analysis of individual or dyadic interactions, we believe that the study of groups adds an additional layer of complexity with respect to how humans...

Automatic multimodal detection of team cohesion in meetings

In this thesis the automatic multimodal detection of social and task cohesion in meetings is studied. The presence of social and task cohesion has positive benefits on employee well-being, creativity and productiveness, and can therefore be used to assess meeting quality. Conversational partners imitate each other's body language and speech...

Group interaction frontiers in technology

Over the last decade, the study of group behavior for multimodal interaction technologies has increased. However, we believe that despite its potential benefits on society, there could be more activity in this area. The aim of this workshop is create a forum for more interdisciplinary dialogue on this topic to enable the acceleration of...

Personalised models for speech detection from body movements using transductive parameter transfer

We investigate the task of detecting speakers in crowded environments using a single body worn triaxial accelerometer. Detection of such behaviour is very challenging to model as people’s body movements during speech vary greatly. Similar to previous studies, by assuming that body movements are indicative of speech, we show experimentally, on...

Prediction of Team Cohesion, by examining prosodic mimicry in small group meetings

In this thesis the alignment of speech behavior between team members of small group meetings (3-8 people) and its relation to team cohesion is studied. Since team cohesion is highly related to effectiveness and productivity, automatically estimating cohesion can be a useful tool for assessing the meeting quality. This information can be fed back...

Is automatic facial expression recognition of emotions coming to a dead end?: The rise of the new kids on the block