艺术装置中的实时声音情感识别和互动故事叙述:CALLAS和IRIS的经验和教训

Thurid Vogt, E. André, J. Wagner, Stephen W. Gilroy, Fred Charles, M. Cavazza
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引用次数: 7

摘要

大多数情感识别系统仍然完全依赖于典型的情感声音表达,这些表达可能被唯一地分配给特定的类别。然而,在现实应用中,并不能保证情感以一种原型的方式表达。在本文中,我们报告了在CALLAS项目和IRIS网络的背景下处理非原型情绪时出现的挑战。CALLAS旨在开发互动艺术装置,实时响应表演者和观众的多模态情感输入。IRIS关注的是交互式故事叙述新技术的发展。这两项研究都代表了非原型性的极端情况,因为刺激和对刺激的情绪反应都不能被认为是原型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Real-time vocal emotion recognition in artistic installations and interactive storytelling: Experiences and lessons learnt from CALLAS and IRIS
Most emotion recognition systems still rely exclusively on prototypical emotional vocal expressions that may be uniquely assigned to a particular class. In realistic applications, there is, however, no guarantee that emotions are expressed in a prototypical manner. In this paper, we report on challenges that arise when coping with non-prototypical emotions in the context of the CALLAS project and the IRIS network. CALLAS aims to develop interactive art installations that respond to the multimodal emotional input of performers and spectators in real-time. IRIS is concerned with the development of novel technologies for interactive storytelling. Both research initiatives represent an extreme case of non-prototypicality since neither the stimuli nor the emotional responses to stimuli may be considered as prototypical.
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