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Multimedia Tools and Applications

, Volume 76, Issue 2, pp 2331–2352 | Cite as

Audio-visual emotion recognition using FCBF feature selection method and particle swarm optimization for fuzzy ARTMAP neural networks

  • Davood GharavianEmail author
  • Mehdi Bejani
  • Mansour Sheikhan
Article

Abstract

Humans use many modalities such as face, speech and body gesture to express their feeling. So, to make emotional computers and make the human-computer interaction (HCI) more naturally and friendly, computers should be able to understand human feelings using speech and visual information. In this paper, we recognize the emotions from audio and visual information using fuzzy ARTMAP neural network (FAMNN). Audio and visual systems fuse at decision and feature levels. Finally, the particle swarm optimization (PSO) is employed to determine the optimum values of the choice parameter (α), the vigilance parameters (ρ), and the learning rate (β) of the FAMNN. Experimental results showed that the feature-level and decision-level fusions improve the outcome of unimodal systems. Also PSO improved the recognition rate. By using the PSO-optimized FAMNN at feature level fusion, the recognition rate was improved by about 57 % with respect to the audio system and by about 4.5 % with respect to the visual system. The final emotion recognition rate on the SAVEE database was reached to 98.25 % using audio and visual features by using optimized FAMNN.

Keywords

Audio-visual emotion recognition Particle swarm optimization Fuzzy ARTMAP neural network 

Notes

Acknowledgments

This work was supported by Islamic Azad University-South Tehran Branch under a research project entitled “Audio-Visual Emotion Modeling to Improve human–computer interaction”.

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Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Davood Gharavian
    • 1
    • 2
    Email author
  • Mehdi Bejani
    • 3
  • Mansour Sheikhan
    • 1
  1. 1.Department of Electrical EngineeringIslamic Azad UniversityTehranIran
  2. 2.Department of Electrical EngineeringShahid Beheshti UniversityTehranIran
  3. 3.Islamic Azad UniversityTehranIran

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