Emotion recognition based on physiological changes in music listening

University of Augsburg

PubMed
Indexed incrossrefpubmed

Abstract

Little attention has been paid so far to physiological signals for emotion recognition compared to audiovisual emotion channels such as facial expression or speech. This paper investigates the potential of physiological signals as reliable channels for emotion recognition. All essential stages of an automatic recognition system are discussed, from the recording of a physiological dataset to a feature-based multiclass classification. In order to collect a physiological dataset from multiple subjects over many weeks, we used a musical induction method which spontaneously leads subjects to real emotional states, without any deliberate lab setting. Four-channel biosensors were used to measure electromyogram,…

Citation impact

1,070
total citations
FWCI
16.78
Percentile
100%
References
56
Citations per year

Authors

2

Topics & keywords

Keywords
  • Arousal
  • Computer science
  • Speech recognition
  • Artificial intelligence
  • Pattern recognition (psychology)
  • Emotion classification
  • Support vector machine
  • Emotion recognition
UN Sustainable Development Goals
  • Reduced inequalities
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