• DocumentCode
    3673280
  • Title

    Preliminary Arabic speech emotion classification

  • Author

    Ali Meftah;Sid-Ahmed Selouani;Yousef A. Alotaibi

  • Author_Institution
    College of Computer and Information Sciences, King Saud University, Riyadh, Saudi Arabia
  • fYear
    2014
  • Firstpage
    179
  • Lastpage
    182
  • Abstract
    In this paper, the acoustic features of pitch, intensity, formants, and speech rate are extracted and used to classify the following Arabic speech emotions: neutral, sad, happy, surprised, and angry. Three sentences spoken by four male and four female native Arabic speakers were selected from a newly developed Arabic speech corpus (KSUEmotions). Perception tests using human listeners yielded scores of 87% (male speakers), 84% (female speakers), and 85% (both male and female) accuracy. The best results for the emotion recognition performance were 83%, 56%, and 78% for male, female, and both together, respectively. Anger was the most readily recognized emotion, while happiness was the most challenging to identify. Pitch and intensity features are key in recognizing the Arabic speech emotion of anger.
  • Keywords
    "Speech","Emotion recognition","Feature extraction","Speech recognition","Accuracy","Standards","Acoustics"
  • Publisher
    ieee
  • Conference_Titel
    Signal Processing and Information Technology (ISSPIT), 2014 IEEE International Symposium on
  • ISSN
    2162-7843
  • Type

    conf

  • DOI
    10.1109/ISSPIT.2014.7300584
  • Filename
    7300584