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Multiple Feature Extraction and Hierarchical Classifiers for Emotions Recognition

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Book cover Development of Multimodal Interfaces: Active Listening and Synchrony

Part of the book series: Lecture Notes in Computer Science ((LNISA,volume 5967))

Abstract

The recognition of the emotional states of speaker is a multi-disciplinary research area that has received great interest in the last years. One of the most important goals is to improve the voiced-based human-machine interactions. Recent works on this domain use the proso-dic features and the spectrum characteristics of speech signal, with standard classifier methods. Furthermore, for traditional methods the improvement in performance has also found a limit. In this paper, the spectral characteristics of emotional signals are used in order to group emotions. Standard classifiers based on Gaussian Mixture Models, Hidden Markov Models and Multilayer Perceptron are tested. These classifiers have been evaluated in different configurations with different features, in order to design a new hierarchical method for emotions classification. The proposed multiple feature hierarchical method improves the performance in 6.35% over the standard classifiers.

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Author information

Authors and Affiliations

  1. Centro de I+D en Señales, Sistemas e INteligencia Computacional (SINC(i)) Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral, Ciudad Universitaria, Paraje El Pozo, S3000, Santa Fe, Argentina

    Enrique M. Albornoz, Diego H. Milone & Hugo L. Rufiner

  2. Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), Argentina

    Enrique M. Albornoz, Diego H. Milone & Hugo L. Rufiner

  3. Laboratorio de Cibernética, Fac. de Ingeniería, Universidad Nacional de Entre Ríos, Argentina

    Hugo L. Rufiner

Authors
  1. Enrique M. Albornoz
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  2. Diego H. Milone
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  3. Hugo L. Rufiner
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Editor information

Editors and Affiliations

  1. Second University of Naples, and IIASS, Via Pellegrino, 84019, Vietri sul Mare, SA, Italy

    Anna Esposito

  2. Centre for Language and Communication Studies, Trinity College, The University of Dublin, Dublin 2, Ireland

    Nick Campbell  & Carl Vogel  & 

  3. Department of Computing Science & Mathematics, University of Stirling, FK9 4LA, Stirling, Scotland, UK

    Amir Hussain

  4. Faculty of Electrical Engineering, Mathematics and Computer Science, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands

    Anton Nijholt

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Albornoz, E.M., Milone, D.H., Rufiner, H.L. (2010). Multiple Feature Extraction and Hierarchical Classifiers for Emotions Recognition. In: Esposito, A., Campbell, N., Vogel, C., Hussain, A., Nijholt, A. (eds) Development of Multimodal Interfaces: Active Listening and Synchrony. Lecture Notes in Computer Science, vol 5967. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12397-9_20

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  • DOI: https://doi.org/10.1007/978-3-642-12397-9_20

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12396-2

  • Online ISBN: 978-3-642-12397-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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