Automatic Speech Emotion Recognition using Auditory Models with Binary Decision Tree and SVM


Yuncu E., HACIHABİBOĞLU H., Bozsahin C.

22nd International Conference on Pattern Recognition (ICPR), Stockholm, Sweden, 24 - 28 August 2014, pp.773-778 identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/icpr.2014.143
  • City: Stockholm
  • Country: Sweden
  • Page Numbers: pp.773-778

Abstract

Affective computing is a term for the design and development of algorithms that enable computers to recognize the emotions of their users and respond in a natural way. Speech, along with facial gestures, is one of the primary modalities with which humans express their emotions. While emotional cues in speech are available to an interlocutor in a dyadic conversation setting, their subjective recognition is far from accurate. This is due to the human auditory system which is primarily non-linear and adaptive. An automatic speech emotion recognition algorithm based on a computational model of the human auditory system is described in this paper. The devised system is tested on three emotional speech datasets. The results of a subjective recognition task is also reported. It is shown that the proposed algorithm provides recognition rates that are comparable to those of human raters.