Open Science Research Excellence
@article{(International Science Index):http://waset.org/publications/10004221,
  title    = {Comparing Emotion Recognition from Voice and Facial Data Using Time Invariant Features},
  author    = {Vesna Kirandziska and  Nevena Ackovska and  Ana Madevska Bogdanova},
  country   = {Macedonia},
  institution={Saints Cyril and Methodius University of Skopje},
  abstract  = {The problem of emotion recognition is a challenging problem. It is still an open problem from the aspect of both intelligent systems and psychology. In this paper, both voice features and facial features are used for building an emotion recognition system. A Support Vector Machine classifiers are built by using raw data from video recordings. In this paper, the results obtained for the emotion recognition are given, and a discussion about the validity and the expressiveness of different emotions is presented. A comparison between the classifiers build from facial data only, voice data only and from the combination of both data is made here. The need for a better combination of the information from facial expression and voice data is argued.
},
    journal   = {International Journal of Computer, Electrical, Automation, Control and Information Engineering},  volume    = {10},
  number    = {5},
  year      = {2016},
  pages     = {823 - 827},
  ee        = {http://waset.org/publications/10004221},
  url       = {http://waset.org/Publications?p=113},
  bibsource = {http://waset.org/Publications},
  issn      = {eISSN:1307-6892},
  publisher = {World Academy of Science, Engineering and Technology},
  index     = {International Science Index 113, 2016},
}