Discrimination Capability of Prosodic and Spectral Features for Emotional Speech Recognition

  • V. Delic University of Novi Sad
  • M. Bojanic University of Novi Sad
  • M. Gnjatovic University of Novi Sad
  • M. Secujski University of Novi Sad
  • S. T. Jovicic University of Belgrade
Keywords: Emotional speech recognition, prosodic features, spectral features


The paper addresses the research question of automatic emotional speech recognition for Serbian. It integrates two research issues: (i) selection of an appropriate feature set, and (ii) investigation of different classification techniques. The paper reports a set of experiments with three feature sets: (i) the prosodic feature set, (ii) the spectral feature set, and (iii) the set of both spectral and prosodic features. The linear Bayes, the perceptron rule and the kNN classifier were considered in all three experiments. The experimental results show that the highest recognition accuracy of 91.5 % was obtained with the third feature set using the linear Bayes classifier.

DOI: http://dx.doi.org/10.5755/j01.eee.18.9.2806