Abstract
Conference Title: 2014 IEEE International Symposium on Signal Processing and Information Technology (ISSPIT) Conference Start Date: 2014, Dec. 15 Conference End Date: 2014, Dec. 17 Conference Location: Noida, India 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.