Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals

@article{VsquezCorrea2014EvaluationOW,
  title={Evaluation of wavelet measures on automatic detection of emotion in noisy and telephony speech signals},
  author={Juan Camilo V{\'a}squez-Correa and Nicanor Garc{\'i}a and Jesus Francisco Vargas Bonilla and Juan R. Orozco-Arroyave and Juli{\'a}n D. Arias-Londo{\~n}o and M. O. Lucia Quintero},
  journal={2014 International Carnahan Conference on Security Technology (ICCST)},
  year={2014},
  pages={1-6}
}
Detection of emotion in humans from speech signals is a recent research field. One of the scenarios where this field has been applied is in situations where the human integrity and security are at risk. In this paper we are propossing a set of features based on the Teager energy operator, and several entropy measures obtained from the decomposition signals from discrete wavelet transform to characterize different types of negative emotions such as anger, anxiety, disgust, and desperation. The… CONTINUE READING

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