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Can an Affect-Sensitive System Afford to Be Context Independent?

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Modeling and Using Context (CONTEXT 2017)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10257))

Abstract

There has been a wave of interest in affect recognition among researchers in the field of affective computing. Most of these research use a context independent approach. Since humans may misunderstand other’s observed facial, vocal, or body behavior without any contextual knowledge, we question whether any of these human-centric affect-sensitive systems can be robust enough without any contextual knowledge. To answer this question, we conducted a study using previously studied audio files in three different settings; these include: no contextual indication, one level of contextual knowledge (either action or relationship/environment), and two levels of contextual knowledge (both action and relationship/environment). Our work confirms that indeed the contextual knowledge can improve recognition of human emotion.

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Authors and Affiliations

  1. Intelligent System Lab, Department of Computer Science, University of Central Florida, Orlando, FL, USA

    Andreas Marpaung & Avelino Gonzalez

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  1. Andreas Marpaung
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  2. Avelino Gonzalez
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Correspondence to Andreas Marpaung .

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Editors and Affiliations

  1. Pierre and Marie Curie University , Paris, France

    Patrick Brézillon

  2. University of Maine , Orono, Maine, USA

    Roy Turner

  3. University of Genoa , Genoa, Italy

    Carlo Penco

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Marpaung, A., Gonzalez, A. (2017). Can an Affect-Sensitive System Afford to Be Context Independent?. In: Brézillon, P., Turner, R., Penco, C. (eds) Modeling and Using Context. CONTEXT 2017. Lecture Notes in Computer Science(), vol 10257. Springer, Cham. https://doi.org/10.1007/978-3-319-57837-8_38

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  • DOI: https://doi.org/10.1007/978-3-319-57837-8_38

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