Zobrazeno 1 - 10
of 747
pro vyhledávání: '"ANDRÉ, Elisabeth"'
Autor:
Vassoyan, Jean, Schütt, Anan, Vie, Jill-Jênn, Lekshmi-Narayanan, Arun-Balajiee, André, Elisabeth, Vayatis, Nicolas
Massive Open Online Courses (MOOCs) have greatly contributed to making education more accessible. However, many MOOCs maintain a rigid, one-size-fits-all structure that fails to address the diverse needs and backgrounds of individual learners. Learni
Externí odkaz:
http://arxiv.org/abs/2411.11520
Autor:
Aicher, Annalena Bea, Matsuda, Yuki, Yasumoto, Keichii, Minker, Wolfgang, André, Elisabeth, Ultes, Stefan
Engaging in discussions that involve diverse perspectives and exchanging arguments on a controversial issue is a natural way for humans to form opinions. In this process, the way arguments are presented plays a crucial role in determining how engaged
Externí odkaz:
http://arxiv.org/abs/2411.11102
Non-verbal behavior is a central challenge in understanding the dynamics of a conversation and the affective states between interlocutors arising from the interaction. Although psychological research has demonstrated that non-verbal behaviors vary ac
Externí odkaz:
http://arxiv.org/abs/2409.13726
Autor:
Chehayeb, Lara, Bhuvaneshwara, Chirag, Anglet, Manuel, Hilpert, Bernhard, Meyer, Ann-Kristin, Tsovaltzi, Dimitra, Gebhard, Patrick, Biermann, Antje, Auchtor, Sinah, Lauinger, Nils, Knopf, Julia, Kaiser, Andreas, Kersting, Fabian, Mehlmann, Gregor, Lingenfelser, Florian, André, Elisabeth
Teachers in challenging conflict situations often experience shame and self-blame, which relate to the feeling of incompetence but may externalise as anger. Sensing mixed signals fails the contingency rule for developing affect regulation and may res
Externí odkaz:
http://arxiv.org/abs/2409.12968
Autor:
Müller, Philipp, Balazia, Michal, Baur, Tobias, Dietz, Michael, Heimerl, Alexander, Penzkofer, Anna, Schiller, Dominik, Brémond, François, Alexandersson, Jan, André, Elisabeth, Bulling, Andreas
Estimating the momentary level of participant's engagement is an important prerequisite for assistive systems that support human interactions. Previous work has addressed this task in within-domain evaluation scenarios, i.e. training and testing on t
Externí odkaz:
http://arxiv.org/abs/2408.16625
Autor:
Mertes, Silvan, Don, Daksitha Withanage, Grothe, Otto, Kuch, Johanna, Schlagowski, Ruben, André, Elisabeth
Modern TTS systems are capable of creating highly realistic and natural-sounding speech. Despite these developments, the process of customizing TTS voices remains a complex task, mostly requiring the expertise of specialists within the field. One rea
Externí odkaz:
http://arxiv.org/abs/2408.12170
Autor:
Müller, Philipp, Heimerl, Alexander, Hossain, Sayed Muddashir, Siegel, Lea, Alexandersson, Jan, Gebhard, Patrick, André, Elisabeth, Schneeberger, Tanja
Human emotions are often not expressed directly, but regulated according to internal processes and social display rules. For affective computing systems, an understanding of how users regulate their emotions can be highly useful, for example to provi
Externí odkaz:
http://arxiv.org/abs/2408.04420
Understanding human behavior is a fundamental goal of social sciences, yet its analysis presents significant challenges. Conventional methodologies employed for the study of behavior, characterized by labor-intensive data collection processes and int
Externí odkaz:
http://arxiv.org/abs/2407.13408
Autor:
Arora, Rhythm, Prajod, Pooja, Nicora, Matteo Lavit, Panzeri, Daniele, Tauro, Giovanni, Vertechy, Rocco, Malosio, Matteo, André, Elisabeth, Gebhard, Patrick
Individuals with diverse motor abilities often benefit from intensive and specialized rehabilitation therapies aimed at enhancing their functional recovery. Nevertheless, the challenge lies in the restricted availability of neurorehabilitation profes
Externí odkaz:
http://arxiv.org/abs/2406.12035
The limited size of pain datasets are a challenge in developing robust deep learning models for pain recognition. Transfer learning approaches are often employed in these scenarios. In this study, we investigate whether deep learned feature represent
Externí odkaz:
http://arxiv.org/abs/2406.11808