Employing Fujisaki’s Intonation Model Parameters for Emotion Recognition

Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3955)


In this paper we are introducing the employment of features extracted from Fujisaki’s parameterization of pitch contour for the task of emotion recognition from speech. In evaluating the proposed features we have trained a decision tree inducer as well as the instance based learning algorithm. The datasets utilized for training the classification models, were extracted from two emotional speech databases. Fujisaki’s parameters benefited all prediction models with an average raise of 9,52% in the total accuracy.


Emotion Recognition Emotion Category Pitch Contour Emotional Speech Total Accuracy 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  1. 1.Wire Communication Laboratory, Electrical and Computer Engineering Dept.University of PatrasRion, PatrasGreece

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