The AffectToolbox: Affect Analysis for Everyone

Silvan Mertes, Dominik Schiller, Michael Dietz, Elisabeth André, Florian Lingenfelser
2/23/2024
cs.HCcs.AIcs.LG

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Abstract

In the field of affective computing, where research continually advances at a rapid pace, the demand for user-friendly tools has become increasingly apparent. In this paper, we present the AffectToolbox, a novel software system that aims to support researchers in developing affect-sensitive studies and prototypes. The proposed system addresses the challenges posed by existing frameworks, which often require profound programming knowledge and cater primarily to power-users or skilled developers. Aiming to facilitate ease of use, the AffectToolbox requires no programming knowledge and offers its functionality to reliably analyze the affective state of users through an accessible graphical user interface. The architecture encompasses a variety of models for emotion recognition on multiple affective channels and modalities, as well as an elaborate fusion system to merge multi-modal assessments into a unified result. The entire system is open-sourced and will be publicly available to ensure easy integration into more complex applications through a well-structured, Python-based code base - therefore marking a substantial contribution toward advancing affective computing research and fostering a more collaborative and inclusive environment within this interdisciplinary field.

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Cite this paper

@article{mertes2024affecttoolbox,
  title  = {The AffectToolbox: Affect Analysis for Everyone},
  author = {Silvan Mertes and Dominik Schiller and Michael Dietz and Elisabeth André and Florian Lingenfelser},
  year   = {2024},
  eprint = {2402.15195},
  archivePrefix = {arXiv},
  url    = {http://arxiv.org/abs/2402.15195v1}
}

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