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.

翻译：在情感计算领域研究持续快速发展的背景下，对用户友好型工具的需求日益凸显。本文提出新型软件系统AffectToolbox，旨在支持研究人员开发情感感知研究原型。该系统有效应对现有框架的挑战——现有解决方案往往需要深厚的编程知识，主要面向高级用户或专业开发人员。为促进易用性，AffectToolbox无需编程基础，通过直观的图形用户界面即可可靠分析用户情感状态。其架构整合了多情感通道与模态的情感识别模型，并配备精细融合系统，可将多模态评估结果整合为统一输出。整个系统采用开源模式，基于结构清晰的Python代码库公开发布，确保可便捷集成至复杂应用中——这标志着情感计算研究的重要突破，为该交叉学科领域营造更协作、更包容的研究环境。