ICMI-MLMI

The consumption of a meal is not just a bodily requirement but can also carry significant symbolic meaning. Solo dining is often contrasted to a shared eating experience and portrayed as an inferior way of eating a meal due to lacking essential social ...

Automatic speech fluency prediction has been mainly approached from the perspective of computer aided language learning, where the system tends to predict ratings similar to those of the human experts. Speech fluency prediction, however, can be ...

Plastic changes with intrinsic dynamics in synaptic efficacy underlie the cellular level of expression of brain functions regarding multimodal information processing. Among diverse plasticity mechanisms, synaptic scaling exerts indispensable effects on ...

Supervised learning relies on the availability and reliability of the labels used to train computational models. In research areas such as Affective Computing and Social Signal Processing, such labels are usually extracted from multiple self- and/or ...

An important milestone for any agent in interaction with humans on a regular basis is to achieve natural and efficient methods of communication. Such strategies should be derived on the hallmarks of human-human interaction. So far, the work in embodied ...

Oral presentation skills are essential for most people’s academic and career development. However, due to public speaking anxiety, many people find oral presentations challenging and often avoid them to the detriment of their careers. Public speaking ...

Although the terms mood and emotion are closely related and often used interchangeably, they are distinguished based on their duration, intensity and attribution. To date, hardly any computational models have (a) examined mood recognition, and (b) ...

Prosodic prominence prediction is an important task in the area of speech processing and especially forms an essential part of modern text-to-speech systems. Previous work has broadly focused on acoustic and linguistic features (such as syntactic and ...

High-rise concrete structures and crowded public spaces are familiar scenes in today’s fast-paced world, resulting in decreased restorative time for humans with nature. Therefore, interior designers and architects have strived to amalgamate nature-...

Aesthetic highlight detection is a challenge for understanding affective processes underlying emotional movie experience. Aesthetic highlights in movies are scenes with aesthetic values and attributes in terms of form and content. Deep understanding of ...

Recent technological advancements have boosted the usage of virtual interviewing platforms where the candidates interact with a virtual interviewing agent or an avatar that has human-like behavior instead of face-to-face interviews. As a result, it is ...

Natural interaction with human-like embodied agents, such as social robots or virtual agents, relies on the generation of realistic non-verbal behaviours, including body language, gaze and facial expressions. Humans can read and interpret somatic ...

In this article, we present two models to jointly and automatically generate the head, facial and gaze movements of a virtual agent from acoustic speech features. Two architectures are explored: a Generative Adversarial Network and an Adversarial ...

In spoken interaction, humans constantly display and interpret each others’ state of understanding. For an embodied agent, displaying its internal state of understanding in an efficient manner can be an important means for making a user-interaction ...

This paper describes FineMotion’s gesture generating system entry for the GENEA Challenge 2022. Our system is based on auto-regressive approach imitating recurrent cell. Combined with a special windowed auto-encoder and training approach this system ...

A critical component of effective communication is the ability to project confidence. In video presentations (e.g., video interviews), there are many factors that influence perceived confidence by a listener. Advances in computer vision, speech ...

Multimodal learning analytics can enrich interaction data with contextual information through mobile sensing. Information about, for example, the physical environment, movement, physiological signals, or smart wearable usage. Through the use of smart ...

Conducting psychophysiological investigations outside of lab settings has a lot of potential for academic applications as well as for industries concerned about the quality of their user and customer experience. Prior work employing in-the-wild ...

Acquiring funding for a startup venture often involves pitching a business idea to potential investors. Insight into the nonverbal behavioral cues that impact the investment decision making process can help entrepreneurs to improve their persuasion ...

When inferring emotions, humans rely on a number of cues, including not only facial expressions, body posture, but also expressor-external, contextual information. The goal of the present study was to compare the impact of such contextual information ...

Emotions recognition systems are trained using noisy human labels and often require heavy preprocessing during multi-modal feature extraction. Using noisy labels in single-task learning increases the risk of over-fitting. Auxiliary tasks could improve ...

There has been growing interest in using deep learning techniques to recognize emotions from speech. However, real-life emotion datasets collected in call centers are relatively rare and small, making the use of deep learning techniques quite ...

In this paper, we present a software-architecture for robot-assisted configurable and autonomous Joint-Attention-Training scenarios to support autism therapy. The focus of the work is the expandability of the architecture for the use of different ...

The use of facial metrics obtained through remote web-based platforms has shown promising results for at-home assessment of facial function in multiple neurological and mental disorders. However, an important factor influencing the utility of the ...

In this paper, we present a visual programming software for enabling non-technical domain experts to create robot-assisted therapy scenarios for multiple robotic platforms. Our new approach is evaluated by comparing it with Choregraphe, the standard ...

We present a scalable multimodal dialog platform for the remote digital assessment and monitoring of schizophrenia. Patients diagnosed with schizophrenia and healthy controls interacted with Tina, a virtual conversational agent, as she guided them ...

Alexithymia is a trait reflecting a person’s difficulty in identifying and expressing their emotions that has been linked to various forms of psychopathology. The identification of alexithymia might have therapeutic, preventive and diagnostic benefits. ...

Advances in computational behavior analysis have the potential to increase our understanding of behavioral patterns and developmental trajectories in neurotypical individuals, as well as in individuals with mental health conditions marked by motor, ...

Conversation requires cooperative social interaction between interlocutors. In particular, active listening through backchannel signaling (hereafter BC) i.e., showing attention through verbal (short responses like “Yeah”) and non-verbal behaviors (e.g. ...

The paper presents a description of the methodological approach for assessing the formation of the emotional sphere of children aged 5-16 years with typical and atypical development. The purpose of the Child's Emotional Development Method (CEDM) is to ...