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
Link To Document :
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