Audio-Based Pre-classification for Semi-automatic Facial Expression Coding

  • Ronald Böck
  • Kerstin Limbrecht-Ecklundt
  • Ingo Siegert
  • Steffen Walter
  • Andreas Wendemuth
Part of the Lecture Notes in Computer Science book series (LNCS, volume 8008)

Abstract

The automatic classification of the users’ internal affective and emotional states is nowadays to be considered for many applications, ranging from organisational tasks to health care. Developing suitable automatic technical systems, training material is necessary for an appropriate adaptation towards users. In this paper, we present a framework which reduces the manual effort in annotation of emotional states. Mainly it pre-selects video material containing facial expressions for a detailed coding according to the Facial Action Coding System based on audio features, namely prosodic and mel-frequency features. Further, we present results of first experiments which were conducted to give a proof-of-concept and to define the parameters for the classifier that is based on Hidden Markov Models. The experiments were done on the EmoRec I dataset.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2013

Authors and Affiliations

  • Ronald Böck
    • 1
  • Kerstin Limbrecht-Ecklundt
    • 2
  • Ingo Siegert
    • 1
  • Steffen Walter
    • 2
  • Andreas Wendemuth
    • 1
  1. 1.Cognitive Systems GroupOtto von Guericke University MagdeburgMagdeburgGermany
  2. 2.Medical PsychologyUlm UniversityUlmGermany

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