• DocumentCode
    3738444
  • Title

    Towards a level assessment system of amusement in speech signals: Amused speech components classification

  • Author

    Kevin El Haddad;H?seyin ?akmak;St?phane Dupont;Thierry Dutoit

  • Author_Institution
    TCTS lab - University of Mons, Belgium
  • fYear
    2015
  • Firstpage
    12
  • Lastpage
    17
  • Abstract
    In this paper, we expose our work on classification of smiled vowels, shaking vowels and laughter syllables. This work is part of a larger framework that aims at assessing the level of amusement in speech using only audio cues. Indeed all of these three categories occur in amused speech and are considered to express a different level of amusement. Four novel features are used to accomplish this task. With only those four features, we are able to obtain good classification results with different systems. Among the compared systems, the best one achieved 21.04% error rate, therefore an accuracy well above chance.
  • Keywords
    "Speech","Feature extraction","Data mining","Emotion recognition","Microphones","Mel frequency cepstral coefficient","Speech recognition"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Information Technology (ISSPIT), 2015 IEEE International Symposium on
  • Type

    conf

  • DOI
    10.1109/ISSPIT.2015.7394252
  • Filename
    7394252