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