ICMI-MLMI

We address the task of automatically predicting group satisfaction in meetings using acoustic, lexical, and turn-taking features. Participant satisfaction is measured using post-meeting ratings from the AMI corpus. We focus on predicting three aspects ...

Engagement/disengagement detection is a challenging task emerging in a range of human-human and human-computer interaction problems. While being important, the issue is still far from being solved and a number of studies involving in-the-wild data have ...

In this work we explore how Augmented Reality annotations can be used as a form of Mixed Reality gesture, how neurophysiological measurements can inform the decision as to whether or not to use such gestures, and whether and how to adapt language when ...

Humans adapt their behaviour to the perceived cognitive load of their dialogue partner, for example, delaying non-essential information. We propose that spoken dialogue systems should do the same, particularly in high-stakes scenarios, such as emergency ...

Research in various fields including psychology, cognition, and medical science deal with eye tracking data to extract information about the intention and cognitive state of a subject. For the extraction of this information, the detection of eye ...

Eye-based monitoring has been suggested as a means to measure mental load in a non-intrusive way. In most cases, the experiments have been conducted in a setting where the user has been mainly passive. This constraint does not reflect applications where ...

Multimodal data is increasingly used in cognitive prediction models to better analyze and predict different user cognitive processes. Classifiers based on such data, however, have different performance characteristics. We discuss in this paper an ...

The cognitive processes that underly expert decision making in medical image interpretation are crucial to the understanding of what constitutes optimal performance. Often, if an anomaly goes undetected, the exact nature of the false negative is not ...

Eye movements hold information about human perception, intention, and cognitive state. Various algorithms have been proposed to identify and distinguish eye movements, particularly fixations, saccades, and smooth pursuits. A major drawback of existing ...

As non-invasive neuroimaging techniques become less expensive and more portable, we have the capability to monitor brain activity during various computer activities. This provides an opportunity to integrate brain data with computer log data to develop ...

Multimer is a new technology that aims to provide a data-driven understanding of how humans cognitively and physically experience spatial environments. By multimodally measuring biosensor data to model how the built environment and its uses influence ...

In this paper we present results from recent experiments that suggest that chess players associate emotions to game situations and reactively use these associations to guide search for planning and problem solving. We report on a pilot experiment with ...

Combining self-reports in which individuals reflect on their thoughts and feelings (Experience Samples) with sensor data collected via ubiquitous monitoring can provide researchers and applications with detailed insights about human behavior and ...

Recent developments in computer vision and the emergence of wearable sensors have opened opportunities for the development of advanced and sophisticated techniques to enable multi-modal user assessment and personalized training which is important in ...